Autonomous robot auto-docking and energy management systems and methods

Abstract
A method for energy management in a robotic device includes providing a base station for mating with the robotic device, determining a quantity of energy stored in an energy storage unit of the robotic device, and performing a predetermined task based at least in part on the quantity of energy stored. Also disclosed are systems for emitting avoidance signals to prevent inadvertent contact between the robot and the base station, and systems for emitting homing signals to allow the robotic device to accurately dock with the base station.
Description
TECHNICAL FIELD

The present invention relates generally to robotic systems and, more specifically, to auto-docking and energy management systems for autonomous robots.


BACKGROUND

Automated robots and robotic devices are becoming more prevalent today and are used to perform tasks traditionally considered mundane, time-consuming, or dangerous. As the programming technology increases, so too does the demand for robotic devices that require a minimum of human interaction for tasks such as robot refueling, testing, and servicing. A goal is a robot that could be configured a single time, which would then operate autonomously, without any need for human assistance or intervention.


Robotic devices and associated controls, navigational systems, and other related systems moving in this direction are being developed. For example, U.S. Pat. No. 6,594,844 discloses a Robot Obstacle Detection System, the disclosure of which is hereby incorporated by reference in its entirety. Additional robot control and navigation systems are disclosed in U.S. patent application Ser. Nos. 10/167,851, 10/056,804, 10/696,456, 10/661,835, and 10/320,729 the disclosures of which are hereby incorporated by reference in their entireties.


Generally, autonomous robotic devices include an on-board power unit (usually a battery) that is recharged at a base or docking station. The types of charging stations and methods used by robots in finding or docking with them (e.g., radio signals, dead reckoning, ultrasonic beams, infrared beams coupled with radio signals, etc.) vary greatly in both effectiveness and application. Wires buried below the surface on which the robot operates are common, but are obviously limited in application, as it is costly to install guide wires within the floor of a building or below a road surface. If installed on the surface, the guide wires may be damaged by the robot itself or other traffic. Moreover, the wires need to be moved when the base station is relocated. A base station that emits a beam or beacon to attract the robotic device is, therefore, more desirable. Such devices, however, still exhibit numerous operational limitations.


Base stations that utilize emitted signals often still require additional safeguards to ensure proper mating between the robot and base station and, therefore, safe and effective charging. Some require mechanical locking devices to prevent dislocation of the robot during charging, or other components such as raised guiding surfaces to direct the robot into contact with the station. Such components can increase the size of the base station while decreasing the aesthetics, important considerations for automated robots directed at the consumer market. An increase in base station size also typically makes unobtrusive placement in the home more difficult and decreases the floor area available for cleaning. Additionally, existing base stations generally lack the ability to protect themselves from contact with the robot during operation, increasing the likelihood of damage to either the station or robot, or dislocation of the base station. Such an unintentional collision may require human intervention to reposition the base station or repair a damaged component.


These limitations are, at present, a hurdle to creating a truly independent autonomous robot, free from human interaction. There is, therefore, a need for a robot and base station that can ensure proper mating regardless of location of the base station. Moreover, a system that can prevent inadvertent dislocation of the base station by eliminating collisions between the station and robot is desirable.


SUMMARY OF THE INVENTION

In one aspect, the invention relates to a method for energy management in a robotic device, the robotic device including at least one energy storage unit and a signal detector. The method includes the steps of: providing a base station for mating with the robotic device, the base station having a plurality of signal emitters including a first signal emitter and a second signal emitter; determining a quantity of energy stored in the energy storage unit, the quantity characterized at least by a high energy level and a low energy level; and performing, by the robotic device, a predetermined task based at least in part on the quantity of energy stored. In various embodiments of the foregoing aspect, coulometry or setting a time period are used to determine the quantity of energy stored or task period of the device.


In other embodiments of the foregoing aspect, the step of performing the predetermined task occurs when the quantity of energy stored exceeds the high energy level, the predetermined task including movement of the robotic device away from the base station in response to reception, by the signal detector, of a base station avoidance signal. Still other embodiments include the step of returning the robotic device to the base station in response to reception, by the signal detector, of a base station homing signal and/or returning the robotic device to the base station when the quantity of energy stored is less than the high energy level. In other embodiments of the foregoing aspect, the step of returning the robotic device to the base station occurs when the quantity of energy stored is less than the low energy level, and wherein the predetermined task includes a reduction in energy use by the robotic device. Various embodiments further include altering a travel characteristic of the robotic device to locate effectively the base station, charging the device upon contact, and/or resuming the predetermined or a different task.


In another aspect, the invention relates to a method of docking a robotic device with a base station that has a plurality of signal emitters, including a first signal emitter and a second signal emitter. The method includes the steps of orienting the robotic device in relation to (i) a first signal transmitted by the first signal emitter and (ii) a second signal transmitted by the second signal emitter, and maintaining an orientation of the robotic device relative to the first and second signals as the robotic device approaches to the base station. Certain embodiments of the method of the foregoing aspect include the steps of detecting, by the robotic device, an overlap between the first signal and the second signal; following, by the robotic device, a path defined at least in part by the signal overlap; and docking the robotic device with the base station. Other related embodiments include reducing the velocity of the robotic device in the step of following the path defined at least in part by the signal overlap.


Various embodiments of the method of the foregoing aspect also include, during the step of docking the robotic device with the base station: detecting, by the robotic device, contact with charging terminals on the base station, and stopping movement of the robotic device. In some embodiments, contact of one or more on-board tactile sensors can be used, additionally or alternatively, to stop movement of the robotic device. Other embodiments include the step of charging fully the robotic device and/or charging the robotic device to one of a plurality of charging levels. Certain embodiments allow for resumption of the predetermined task or a new task upon completion of charging.


In another aspect of the invention, the invention relates to an autonomous system including a base station, that includes charging terminals for contacting external terminals of a robotic device, and a first signal emitter and a second signal emitter. Certain embodiments of the above aspect provide that the first signal emitter transmit a base station avoidance signal and the second signal emitter transmit a base station homing signal. In other embodiments, the homing signal is a pair of signals, which can be either the same or different. The pair of signals may be emitted by a pair of emitters. In some embodiments, the signals may overlap, and may be optical signals.


Certain embodiments of the above aspect further include a robotic device for performing a predetermined task, the robotic device having at least one energy storage unit with an external terminal for contacting the charging terminal, and at least one signal detector. In certain embodiments, the at least one signal detector is adapted to detect at least one optical signal. The robotic device has, in certain embodiments, the capability to distinguish between the signals generated by multiple emitters.


Still other aspects of the current invention relate to an energy manager including: a robotic device having at least one energy storage unit and a signal detector; a base station for mating with the robotic device, the base station having a plurality of signal emitters including a first signal emitter and a second signal emitter; and a processor for determining a quantity of energy stored in the energy storage unit. Certain embodiments of the foregoing aspect use coulometry or set a time period to determine the quantity of energy stored or task period of the device. In still other embodiments the first signal emitter transmits an avoidance signal, thereby restricting a movement of the robotic device to directions away from the base station, and the second signal emitter transmits a homing signal, thereby directing a movement of the robotic device to the base station.


Other aspects of the invention relate to a homing system including a robotic device having a signal detector, and a base station having a first signal emitter and a second signal emitter. Certain embodiments of the foregoing aspect overlap signals transmitted by the first signal emitter and the second signal emitter. Still other embodiments further include charging terminals on the base station, and charging terminals on the robotic device.


An additional aspect of the invention relates to a homing system for a base station including a first signal emitter that transmits a first signal projected outward from the first signal emitter, and a second signal emitter that transmits a second signal projected outward from the second signal emitter, such that the first signal and the second signal overlap. Another aspect relates to an avoidance system for restricting a movement of at least one of a first device and a second device, the avoidance system including a first device that emits a signal, and a second device that receives the signal, thereby restricting the movement of at least one of the first device and the second device.


Still another aspect of the invention relates to a base station, including a base plate and a backstop, for a robotic device including: electrical contacts located on a top side of the base plate; a first signal emitter located on the backstop wherein a signal transmitted by the first signal emitter restricts the robotic device from moving within a predetermined distance of the base station; and a second signal emitter and a third signal emitter, wherein a plurality of signals transmitted by the second signal emitter and the third signal emitter guide at least one electrical contact of the robotic device to contact the at least one electrical contact of the base station.


Another aspect of the invention relates to a method of charging a battery of a device, the method having the steps of providing low power to charging terminals of a charger, detecting presence of the device by monitoring at least one of a predetermined change in and a predetermined magnitude of a parameter associated with the charger, and increasing power to the charging terminals to charge the battery. One embodiment of the method of the above aspect further includes the steps of determining a level of charge in the device, and permitting charging of the battery in the device when the level of charge is below a predetermined threshold.


Still another aspect of the invention relates to a system for charging a mobile device, the system having: a stationary charger comprising first charging terminals, circuitry for detecting presence of the device by monitoring at least one of a predetermined change in and a predetermined magnitude of a parameter associated with the charger, and a mobile device having: a battery, and second charging terminals adapted to mate with first charging terminals. Various embodiments of the above aspect include systems wherein the circuitry determines a level of charge in the battery and controls a power level provided to the first charging terminals. Still other embodiments include systems wherein the circuitry increases the power level provided to the first charging terminals upon measuring a predetermined voltage across the first charging terminals when mated with the second charging terminal.





BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, like reference characters generally refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead generally being placed upon illustrating the principles of the invention. In the following description, various embodiments of the present invention are described with reference to the following drawings, in which:



FIG. 1 is a schematic perspective view a base station in accordance with one embodiment of the invention;



FIG. 2A is a schematic perspective view of an robotic device in accordance with one embodiment of the invention;



FIG. 2B is a schematic side view of the robotic device of FIG. 2A.



FIG. 3 is a schematic perspective view of a representation of robotic device and base station, depicting an avoidance signal in accordance with one embodiment of the invention transmitted by the base station and detected by the robotic device;



FIGS. 4A-4C are schematic perspective views of representations of homing signals in accordance with one embodiment of the invention transmitted by the base station and detected by the robotic device;



FIG. 5 is a schematic perspective view of the robotic device and the base station in a docking or mating position;



FIGS. 6A-6B are flow charts of avoidance algorithms in accordance with one embodiment of the invention;



FIG. 7 is a flow chart of an energy management algorithm in accordance with one embodiment of the invention; and



FIG. 8 depicts an embodiment of the charger circuitry schematic in accordance with one embodiment of the invention.





DETAILED DESCRIPTION


FIG. 1 is a schematic perspective view a base station 10 in accordance with one embodiment of the invention. The base station 10 includes both a substantially horizontal base plate 12 and a substantially vertical backstop 14. The base station 10 may be any of a variety of shapes or sizes, providing sufficient space for the desired components and systems, described below. The base plate 12 is generally parallel to the ground surface on which the base station 10 rests, but may have a slight upwards angle directed toward the backstop 14. By minimizing the angle of rise of the base plate 12, the robotic device (FIGS. 2A-2B) may easily dock with the station 10. Electrical charging contacts 16 are located on a top surface of the base plate 12, allowing them to contact corresponding contacts (FIG. 2B) on the underside of the robotic device. The contacts 16 or the contacts on the robot may be either fixed or compliant. In the depicted embodiment, two contacts 16 (one positive, one negative) are utilized to properly detect a completed circuit when the robot 40 docks with the base station 10. This circuit recognition sequence is described in more detail below. In other embodiments, however, a single contact 16 or more than two contacts may be utilized. An additional contact would provide redundancy in the event that one of the robot contacts becomes damaged, dirty, or obstructed. This would allow the robot to dock and recharge itself properly, even after such an occurrence. Other embodiments utilize two contacts 16 to charge the battery and additional contacts to transmit data and information between the devices.


The contacts 16 are sized and positioned to reliably and repeatably contact the corresponding contacts on the robot. For example, the contacts 16 may be oversized and/or may extend above the base plate 12, e.g., in a domed shape, to ensure contact with the robot contacts. Alternatively, the contacts 16 may be flush-mounted on a base plate 12 with a higher angle of rise or may protrude above a base plate 12 that is flat or has substantially no rise. Depending on the application, the base plate 12 angle of rise may vary from 0° to up to 20° and greater. The embodiment depicted in FIG. 1 also includes a depression 26 in the base plate 12, between the two contacts 16, sized to engage a front caster (FIG. 2B) of the robot. The depression 26, in combination with the configuration of the charging contacts 16, ensures proper alignment and registration between the charging contacts on both the base station 10 and the robot. Alternatively, the depression 26 may contain one or more of the contacts 16 arranged to mate with one or more corresponding contacts on the front caster of the robot.


The backstop 14 provides locations for many of the base station 10 components. Specifically, in the depicted embodiment, the backstop 14 includes a top signal emitter 18, a front signal emitter 20, several indicator LEDs 22, and an AC plug receptacle 24. The top signal emitter 18 generates a first signal, such as an avoidance signal (FIG. 3), in a diffuse region near the base station 10 to prevent generally the robot from coming into inadvertent direct contact with the base station 10 while performing a task, such as vacuuming. The top signal emitter 18 generally utilizes a parabolic reflector to transmit the avoidance signal. In such an embodiment, the avoidance signal is emitted by a single LED directed at a lens whose geometry is determined by rotating a parabola about its focus. This parabolic reflector thus projects the avoidance signal 60 out in a 360° pattern, without the necessity of multiple emitters. A similar configuration can be employed in the detector on the robot, with a single receiver used in place of the single LED.


While the location of the top signal emitter 18 may vary, locating the emitter 18 on top of the backstop 14 transmits the avoidance signal through an uninterrupted 360° field around the base station 10. Alternatively, base stations designed for corner, on-wall, or near-wall installation may project the avoidance signal substantially only along the unobstructed side. The front signal emitter 20 projects one or more additional signals, such as homing beams (FIGS. 4A-4C), to allow the robotic device to orient itself during docking with the base station 10 for recharging or during periods of non-use. Naturally, if properly located on the base station 10, a single emitter may be used to perform the functions of both emitters 18, 20. Both the avoidance signal and homing beams are described in more detail below.



FIGS. 2A-2B are schematic perspective views of a robotic device, such as an autonomous robot 40 adapted to mate with the base station 10. In the following description of the autonomous robot 40, use of the terminology “forward/fore” refers generally to the primary direction of motion of the robot 40, and the terminology fore-aft axis (see reference characters “FA” in FIG. 2A) defines the forward direction of motion (indicated by arrowhead of the fore-aft axis FA), which is coincident with the fore-aft diameter of the robot 40.


In the embodiment depicted, the housing infrastructure 42 of the robot 40 includes a chassis 44, a cover 46, and a displaceable bumper 48. The chassis 44 may be molded from a material such as plastic as a unitary element that includes a plurality of preformed wells, recesses, and structural members for, inter alia, mounting or integrating elements of the various subsystems that operate the robotic device 40. Such subsystems may include a microprocessor, a power subsystem (including one or more power sources for the various subsystems and components), a motive subsystem, a sensor subsystem, and task-specific component subsystems. The cover 46 may be molded from a material such as plastic as a unitary element that is complementary in configuration with the chassis 44 and provides protection of and access to elements and components mounted to the chassis 44. The chassis 44 and the cover 46 are detachably integrated in combination by any suitable means (e.g., screws), and in combination, the chassis 44 and cover 46 form a structural envelope of minimal height having a generally cylindrical configuration that is generally symmetrical along the fore-aft axis FA.


The displaceable bumper 48, which has a generally arcuate configuration, is mounted in movable combination at the forward portion of the chassis 44 to extend outwardly therefrom (the “normal operating position”). The mounting configuration of the displaceable bumper 48 is such that it is displaced towards the chassis 44 (from the normal operating position) whenever the bumper 48 encounters a stationary object or obstacle of predetermined mass (the “displaced position”), and returns to the normal operating position when contact with the stationary object or obstacle is terminated (due to operation of a control sequence which, in response to any such displacement of the bumper 48, implements a “bounce” mode that causes the robot 40 to evade the stationary object or obstacle and continue its task routine).


Mounted on the robotic device 40 are a pair of detectors 50, 52. In this embodiment of the robotic device 40, the detectors 50, 52 receive signals projected from the emitters 18, 20 on the base station 10. In other embodiments, a single detector receives signals from both emitters 18, 20 on the base station 10, or more than two detectors may be used. In certain embodiments, the detectors 50, 52 are standard infrared (“IR”) detector modules, that include a photodiode and related amplification and detection circuitry, in conjunction with an omni-directional lens, where omni-directional refers to a substantially single plane. The IR detector module can be of the type manufactured by East Dynamic Corporation (p/n IRM-8601S). However, any detector, regardless of modulation or peak detection wavelength, can be used as long as the emitters 18, 20 on the base station 10 are adapted to match the detectors 50, 52 on the robot 40. In another embodiment, IR phototransistors may be used with or without electronic amplification elements and may be connected directly to the analog inputs of a microprocessor. Signal processing may then be used to measure the intensity of IR light at the robot 40, which provides an estimate of the distance between the robot 40 and the source of IR light. Alternatively, radio frequencies, magnetic fields, and ultrasonic sensors and transducers may be employed. As shown in FIGS. 2A-2B, at least one detector 50 is mounted at the highest point on the robot 40 and toward the front of the robot 40 as defined by the primary traveling direction, as indicated by an arrow on axis FA.


While the detector 50 is mounted at the highest point of the robot 40 in order to avoid shadows, it is desirable in certain applications to minimize the height of the robot 40 and/or the detector 50 to prevent operational difficulties and to allow the robot 40 to pass under obstacles. In certain embodiments, the detector 50 can be spring-mounted to allow the detector 50 to collapse into the body of the robot 40 when the robot 40 runs under a solid overhanging object.


One of skill in the art will recognize that, in alternative embodiments, multiple detectors can be used. Such an embodiment might include using multiple side-mounted sensors or detectors. Each of the sensors can be oriented in a manner so that a collective field of view of all the sensors corresponds to that of the single, top mounted sensor. Because a single, omni-directional detector is mounted at the highest point of the robot for optimal performance, it is possible to lower the profile of the robot by incorporating multiple, side mounted detectors.


The undercarriage of the robotic device 40 is indicated generally by numeral 54. One or more charging contacts are present in the undercarriage 54, configured in such a location to correspond with the location of the electrical contacts 16 of the base station 10. Generally, the charging contacts on the robotic device mirror those present on the base station 10, regardless of their location or orientation. In certain embodiments, the charging contacts may be larger on either the base station 10 or robot 40, to allow wider compliance in making contact. Also, the motive and task specific components of the robot 40 are located in the undercarriage 54. The motive components may include any combination of motors, wheels, drive shafts, or tracks as desired, based on cost or intended application of the robot 40, all of which are well known in the art. The motive components may include at least one caster 56 which, in this embodiment, drives the robot 40 and mates with the depression 26 on the base plate 12. As the tasks to which the robotic device 40 is suited are virtually unlimited, so too are the components to perform those tasks. For example, the robotic device 40 may be used for floor waxing and polishing, floor scrubbing, ice resurfacing (as typically performed by equipment manufactured under the brand name Zamboni®), sweeping and vacuuming, unfinished floor sanding and stain/paint application, ice melting and snow removal, grass cutting, etc. Any number of components may be required for such tasks, and may each be incorporated into the robotic device 40, as necessary. For simplicity, this application will describe vacuuming as the demonstrative predetermined task. It will be apparent, though, that the energy management and auto-docking functions disclosed herein have wide application across a variety of robotic systems.


The robotic device 40 uses a variety of behavioral modes to vacuum effectively a working area. Behavioral modes are layers of control systems that can be operated in parallel. The microprocessor is operative to execute a prioritized arbitration scheme to identify and implement one or more dominant behavioral modes for any given scenario, based upon inputs from the sensor system. The microprocessor is also operative to coordinate avoidance, homing, and docking maneuvers with the base station 10.


Generally, the behavioral modes for the described robotic device 40 can be characterized as: (1) coverage behavioral modes; (2) escape behavioral modes; and (3) safety behavioral modes. Coverage behavioral modes are primarily designed to allow the robotic device 40 to perform its operations in an efficient and effective manner, while the escape and safety behavioral modes are priority behavioral modes implemented when a signal from the sensor system indicates that normal operation of the robotic device 40 is impaired (e.g., obstacle encountered), or is likely to be impaired (e.g., drop-off detected).


Representative and illustrative coverage behavioral modes (for vacuuming) for the robotic device 40 include: (1) a Spot Coverage pattern; (2) an Obstacle-Following (or Edge-Cleaning) Coverage pattern, and (3) a Room Coverage pattern. The Spot Coverage pattern causes the robotic device 40 to clean a limited area within the defined working area, e.g., a high-traffic area. In a certain embodiments the Spot Coverage pattern is implemented by means of a spiral algorithm (but other types of self-bounded area algorithms, such as polygonal, can be used). The spiral algorithm, which causes outward or inward spiraling movement of the robotic device 40, is implemented by control signals from the microprocessor to the motive system to change the turn radius/radii thereof as a function of time or distance traveled (thereby increasing/decreasing the spiral movement pattern of the robotic device 40).


The robotic device 40 is operated in the Spot Coverage pattern for a predetermined or random period of time, for a predetermined or random distance (e.g., a maximum spiral distance) and/or until the occurrence of a specified event, e.g., activation of one or more of the obstacle detection systems (collectively a transition condition). Once a transition condition occurs, the robotic device 40 can implement or transition to a different behavioral mode, e.g., a Straight. Line behavioral mode (in one embodiment of the robotic device 40, the Straight Line behavioral mode is a low priority, default behavior that propels the robot in an approximately straight line at a preset velocity of approximately 0.306 m/s) or a Bounce behavioral mode in combination with a Straight Line behavioral mode. The Bounce behavioral mode is a basic function that allows the robot 40 to evade a stationary object or obstacle and continue its task routine. Avoidance is achieved by executing a series of turns until the obstacle is no longer detected (i.e., the bumper 48 is no longer compressed).


If the transition condition is the result of the robotic device 40 encountering an obstacle, the robotic device 40 can take other actions in lieu of transitioning to a different behavioral mode. The robotic device 40 can momentarily implement a behavioral mode to avoid or escape the obstacle and resume operation under control of the spiral algorithm (i.e., continue spiraling in the same direction). Alternatively, the robotic device 40 can momentarily implement a behavioral mode to avoid or escape the obstacle and resume operation under control of the spiral algorithm (but in the opposite direction—reflective spiraling).


The Obstacle-Following. Coverage pattern causes the robotic device 40 to clean the perimeter of the defined working area, e.g., a room bounded by walls, and/or the perimeter of an obstacle (e.g., furniture) within the defined working area. Preferably, the robotic device 40 utilizes an obstacle-following system to continuously maintain its position with respect to an obstacle, such as a wall or a piece of furniture, so that the motion of the robotic device 40 causes it to travel adjacent to and concomitantly clean along the perimeter of the obstacle. Different embodiments of the obstacle-following system can be used to implement the Obstacle-Following behavioral pattern.


In certain embodiments, the obstacle-following system is operated to detect the presence or absence of the obstacle. In an alternative embodiment, the obstacle-following system is operated to detect an obstacle and then maintain a predetermined distance between the obstacle and the robotic device 40. In the first embodiment, the microprocessor is operative, in response to signals from the obstacle-following system, to implement small clockwise or counterclockwise turns to maintain its position with respect to the obstacle. The robotic device 40 implements a small clockwise turn when the robotic device 40 transitions from obstacle detection to non-detection (reflection to non-reflection) or to implement a small counterclockwise turn when the robotic device 40 transitions from non-detection to detection (non-reflection to reflection). Similar turning behaviors are implemented by the robotic device 40 to maintain the predetermined distance from the obstacle.


The robotic device 40 is operated in the Obstacle-Following behavioral mode for a predetermined or random period of time, for a predetermined or random distance (e.g., a maximum or minimum distance) and/or until the occurrence of a specified event, e.g., activation of one or more of the obstacle detection system a predetermined number of times (collectively a transition condition). In certain embodiments, the microprocessor will cause the robotic device 40 to implement an Align behavioral mode upon activation of the obstacle-detection system in the Obstacle-Following behavioral mode, wherein the robot 40 implements a minimum angle counterclockwise turn to align the robotic device 40 with the obstacle.


The Room Coverage pattern can be used by the robotic device 40 to clean any defined working area that is bounded by walls, stairs, obstacles or other barriers (e.g., a virtual wall unit that prevents the robotic device 40 from passing through an otherwise unbounded zone). Certain embodiments of the Room Coverage pattern include the Random-Bounce behavioral mode in combination with the Straight Line behavioral mode. Initially, the robotic device 40 travels under control of the Straight-Line behavioral mode (wheels operating at the same rotational speed in the same direction) until an obstacle is encountered. The obstacle may be indicated by physical contact with a wall or detection of the base station avoidance signal. Upon activation of one or more of the obstacle detection system, the microprocessor is operative to compute an acceptable range of new directions based upon the obstacle detection system activated. The microprocessor selects a new heading from within the acceptable range and implements a clockwise or counterclockwise turn to achieve the new heading with minimal movement. In some embodiments, the new turn heading may be followed by forward movement to increase the cleaning efficiency of the robotic device 40. The new heading may be randomly selected across the acceptable range of headings, or based upon some statistical selection scheme, such as Gaussian distribution. In other embodiments of the Room Coverage behavioral mode, the microprocessing unit can be programmed to change headings randomly or at predetermined times, without input from the sensor system.


The robotic device 40 is operated in the Room Coverage behavioral mode for a predetermined or random period of time, for a predetermined or random distance (e.g., a maximum or minimum distance) and/or until the occurrence of a specified event, e.g., activation of the obstacle-detection system a predetermined number of times (collectively a transition condition).


Certain embodiments of the robotic device 40 include four escape behavioral modes: a Turn behavioral mode, an Edge behavioral mode, a Wheel Drop behavioral mode, and a Slow behavioral mode. One skilled in the art will appreciate that other behavioral modes can be utilized by the robotic device 40. One or more of these behavioral modes may be implemented, for example, in response to a current rise in one of the task components (indicating some sort of interference), the forward bumper 48 being in compressed position for determined time period, or detection of a wheel-drop event.


In the Turn behavioral mode, the robotic device 40 turns in place in a random direction, starting at higher velocity (e.g., twice normal turning velocity) and decreasing to a lower velocity (one-half normal turning velocity), i.e., small panic turns and large panic turns, respectively. Low panic turns are preferably in the range of 45° to 90°, large panic turns are preferably in the range of 90° to 270°. The Turn behavioral mode prevents the robotic device 40 from becoming stuck on surface impediments (e.g., high spot on carpet), from becoming stuck under other obstacles (e.g., an overhang), or from becoming trapped in a confined area.


In the Edge behavioral mode, the robotic device 40 follows the edge of an obstacle unit it has turned through a predetermined number of degrees, without activation of any of the obstacle detection units, or until the robotic device 40 has turned through a predetermined number of degrees, since initiation of the Edge behavioral mode. The Edge behavioral mode allows the robotic device 40 to move through the smallest possible openings to escape from confined areas.


In the Wheel Drop behavioral mode, the microprocessor reverses the direction of the main wheel drive assemblies momentarily, then stops them. If the activated wheel drop sensor deactivates within a predetermined time, the microprocessor then reimplements the behavioral mode that was being executed prior to the activation of the wheel drop sensor.


In response to certain events, e.g., activation of a wheel drop sensor or a cliff detector, the Slow behavioral mode is implemented to slow down the robotic device 40 for a predetermined distance and then ramp back up to its normal operating speed.


When a safety condition is detected by the sensor subsystem, e.g., a series of task component or wheel stalls that cause the corresponding electric motors to be temporarily cycled off, or a wheel drop sensor or a cliff detection sensor activated for greater that a predetermined period of time, the robotic device 40 is generally cycled to an off state. In addition, an audible alarm may be generated.


The foregoing description of typical behavioral modes for the robotic device 40 are intended to be representative of the types of operating modes that can be implemented by the robotic device 40. One skilled in the art will appreciate that the behavioral modes described above can be implemented in other combinations and other modes can be defined to achieve a desired result in a particular application.


A navigational control system may be used advantageously in combination with the robotic device 40 to enhance the cleaning efficiency thereof, by adding a deterministic component (in the form of a control signal that controls the movement of the robotic device 40), to the motion algorithms, including random motion, autonomously implemented by the robotic device 40. The navigational control system operates under the direction of a navigation control algorithm. The navigation control algorithm includes a definition of a predetermined triggering event.


Broadly described, the navigational control system, under the direction of the navigation control algorithm, monitors the movement activity of the robotic device 40. In one embodiment, the monitored movement activity is defined in terms of the “position history” of the robotic device 40, as described in further detail below. In another embodiment, the monitored movement activity is defined in terms of the “instantaneous position” of the robotic device 40.


The predetermined triggering event is a specific occurrence or condition in the movement activity of the robotic device 40. Upon the realization of the predetermined triggering event, the navigational control system operates to generate and communicate a control signal to the robotic device 40. In response to the control signal, the robotic device 40 operates to implement or execute a conduct prescribed by the control signal, i.e., the prescribed conduct. This prescribed conduct represents a deterministic component of the movement activity of the robotic device 40.


While the robotic device 40 is vacuuming, it will periodically approach the stationary base station 10. Contact with the base station 10 could damage or move the base station into an area that would make docking impossible. Therefore, avoidance functionality is desirable. To avoid inadvertent contact, the base station 10 may generate an avoidance signal 60, as depicted in FIG. 3. The avoidance signal 60 is shown being transmitted from the emitter 18 on the top of the backstop 14. The radial range of the avoidance signal 60 from the base station 10 may vary, depending on predefined factory settings, user settings, or other considerations. At a minimum, the avoidance signal 60 need only project a distance sufficient to protect the base station 10 from unintentional contact with the robot 40. The avoidance signal 60 range can extend from beyond the periphery of the base station 10, to up to and beyond several feet from the base station 10, depending on the application.


Here, the avoidance signal 60 is depicted as an omni-directional (i.e., single'plane) infrared beam, although other signals are contemplated, such as a plurality of single stationary beams or signals. If stationary beams are used, however, a sufficient number could provide adequate coverage around the base station 10 to increase the chances of the robotic device 40 encountering them. When the detector 50 of the robotic device 40 receives the avoidance signal 60 from the emitter 18, the robotic device 40 can alter its course, as required, to avoid the base station 10. Alternatively, if the robotic device 40 is actively or passively seeking the base station 10 (for recharging or other docking purposes), it can alter its course toward the base station 10, such as by circling the base station 10, in such a way to increase the chances of encountering the homing signals described with respect to FIGS. 4A-4B below.


In certain embodiments, a collimated IR emitter is used, such as Waitrony p/n IE-320H. Because of potential interference from sunlight and other IR sources, most IR devices, such as remote controls, personal digital assistants and other IR communication devices, emit signals that may be modulated. Herein, the emitters 18, 20 modulate the beams at 38 kHz. In an embodiment of the present invention, additional modulation of the beams at a frequency, for example 500 Hz, different from the frequency of common IR bit streams, prevents interference with other IR equipment. Generally, the avoidance signal 60 is coded, as are the homing signals 62, 64. The bit encoding method as well as binary codes are selected such that the robot 40 can detect the presence of each signal, even if the robot 40 receives multiple codes simultaneously.


Whenever a measurable level of IR radiation from the avoidance signal 60 strikes the detector 50, the robot's IR avoidance behavior is triggered. In one embodiment, this behavior causes the robot 40 to spin in place to the left until the IR signal falls below detectable levels. The robot 40 then resumes its previous motion. Spinning left is desired in certain systems because, by convention, the robot may attempt to keep all objects to its right during following operations. The robot's avoidance behavior is consistent with its other behaviors if it spins left on detecting the avoidance signal 60. In one embodiment, the detector 50 acts as a gradient detector. When the robot 40 encounters a region of higher IR intensity, the robot 40 spins in place. Because the detector 50 is mounted at the front of the robot 40 and because the robot 40 does not move backward, the detector 50 always “sees” the increasing IR intensity before other parts of the robot 40. Thus, spinning in place causes the detector 50 to move to a region of decreased intensity. When the robot 40 next moves forward, it necessarily moves to a region of decreased IR intensity—away from the avoidance signal 60.


In other embodiments, the base station 10 includes multiple coded emitters at different power levels or emitters that vary their power level using a system of time multiplexing. These create concentric coded signal rings which enable the robot 40 to navigate towards the base station 10 from far away in the room. Thus, the robot 40 would be aware of the presence of the base station 10 at all times, facilitating locating the base station 10, docking, determining how much of the room has been cleaned, etc. Alternatively, the robot 40 uses its motion through the IR field to measure a gradient of IR energy. When the sign of the gradient is negative (i.e., the detected energy is decreasing with motion), the robot 40 goes straight (away from the IR source). When the sign of the gradient is positive (energy increasing), the robot 40 turns. The net effect is to implement a “gradient descent algorithm,” with the robot 40 escaping from the source of the avoidance signal 60. This gradient method may also be used to seek the source of emitted signals. The concentric rings at varying power levels facilitate this possibility even without a means for determination of the raw signal strength.


A flowchart of one embodiment of the control logic of the avoidance behavior 100 is shown in FIG. 6A. The robot 40 determines whether the signal 110 detected by the detector 50 is an avoidance signal 60. If an avoidance signal 60 is detected, the robot 40 chooses a turning direction 120. The robot 40 then begins to turn in the chosen direction until the avoidance signal 60 is no longer detected 130. Once the avoidance signal 60 is no longer detected, the robot 40 continues turning for an additional amount 140, such as 20°, or the robot may turn randomly between 0° and 135°.


While in flowchart step 120, the direction selection algorithm 120a, illustrated in the flowchart shown in FIG. 6B, is used. The robot's control logic keeps track of the robot's discrete interactions with the beam. The robot 40 first increments a counter by one 122. On odd numbered interactions, the robot 40 chooses a new turning direction randomly 124, 126; on even numbered interactions, the robot 40 again uses its most recent turning direction. In the alternative, the robot 40 may choose which direction to turn at random. It will continue to turn in that direction until it has moved a sufficient distance.


In other embodiments, the robot 40 can always turn in a single direction or choose a direction randomly. When the robot 40 always turns in one direction, it may get stuck in a loop by turning away from the beam, bumping into another obstacle in a room, turning back toward the beam, seeing the beam again, turning away, bumping again, ad infinitum. Moreover, when the robot 40 only turns in a single direction, it consequently may fail to vacuum certain areas of the floor. Thus, where the robot's task is to complete work evenly throughout a room, a single turning direction may not be optimal. If the direction is chosen purely randomly, the robot 40 may turn back and forth often, as it encounters the beam.


Again referring to FIG. 6A, in the embodiment of step 140, the robot 40 turns an additional 20° from the point at which the avoidance signal 60 is lost. The arc of the turn can be varied for the particular robot 40 and application. The additional turn helps to prevent the robot 40 from re-encountering the avoidance signal 60 immediately after first encountering it. For various applications, the amount of additional movement (linear or turning) can be a predetermined distance, angle or time, or in the alternative may include a random component. In still other embodiments, the robot's avoidance behavior may include reversing the robot's direction until the avoidance signal 60 is no longer detected, or as described above, the robot may turn randomly between 0° and 135° after losing the avoidance signal 60.



FIGS. 4A-4C depict the robotic device 40 in various stages of seeking the base station 10 by using the homing signals 62, 64. The robotic device 40 may seek the base station 10 when it detects the need to recharge its battery, or when it has completed vacuuming the room. As described above, once the robotic device 40 detects the presence of the avoidance signal 60 (and therefore the base station 10), it can move as required to detect the homing signals 62, 64. As with the avoidance signal 60 above, the projected range and orientation of the homing signals 62, 64 may be varied, as desired. It should be noted however, that longer signals can increase the chance of the robot 40 finding the base station 10 efficiently. Longer signals can also be useful if the robotic device 40 is deployed in a particularly large room, where locating the base station 10 randomly could be inordinately time consuming. Homing signal 62, 64 ranges that extend from approximately six inches beyond the front of the base plate 12, to up to and beyond several feet beyond the base plate 12 are contemplated, depending on application. Naturally, the angular width of the homing signals 62, 64 may vary depending on application, but angular widths in the range of 5° to up to and beyond 60° are contemplated. A gradient behavior as described above can also be used to aid the robot in seeking out the base station.


In addition to operating as navigational beacons, homing signals 62, 64 (and even the avoidance signal 60) may also be used to transmit information, including programming data, fail safe and diagnostic information, docking control data and information, maintenance and control sequences, etc. In such an embodiment, the signals can provide the control information, dictating the robot's reactions, as opposed to the robot 40 taking certain actions upon contacting certain signals from the base station 10. In that case, the robot 40 functions as more of a slave to the base station 10, operating as directed by the signals sent.


The robot 40 performs its docking with the base station 10 accurately and repeatably, without the need for gross mechanical guidance features. The two homing signals 62, 64 are distinguishable by the robotic device, for example as a red signal 62 and a green signal 64. IR beams are generally used to produce the signals and, as such, are not visible. The color distinction is given for illustrative purposes only, and any “color” (i.e., signal bit pattern) may be used, provided the robotic device 40 recognizes which signal to orient a particular side. Alternatively, the signals 62, 64 may be distinguished by using different wavelengths or by using different carrier frequencies (e.g., 380 kHz versus 38 kHz, etc.).


Thus, when the robotic device 40 wants or needs to dock, if the detector 50 receives the red signal 62 transmitting from the base station 10, it moves to keep the red signal 62 on the robot's right side; if it detects the green signal 64 transmitting from the base station 10, it moves to keep the green signal 64 on the robot's left side. Where the two signals overlap (the “yellow” zone 66), the robot 40 knows that the base station 10 is nearby and may then dock. Such a system may be optimized to make the yellow zone 66 as thin as practicably possible, to ensure proper orientation and approach of the robot 40 and successful docking. Alternatively, the red signal 62 and green signal 64 may be replaced by a single signal, which the robot 40 would follow until docked.



FIGS. 4A-4C depict, at various stages, a docking procedure utilizing two signals. In FIG. 4A, the detector 50 is in the green or left signal 64 field, and thus the robotic device 40 will move towards the right, in direction MR in an effort to keep that green signal 64 to the left of the robot 40 (in actuality, the robot 40 moves to keep the green signal 64 to the left of the detector 50). Similarly, in FIG. 4B, the detector 50 is in the red or right signal 62 field, and thus the robotic device 40 will move towards the left, in direction ML in an effort to keep that red signal 64 to the right of the detector 50. Last, in FIG. 4C, the detector 50 has encountered yellow zone 66. At this point, the robotic device 40 will move in direction MF directly towards the base station 10. While approaching the base station 10, the robotic device 40 may slow its speed of approach and/or discontinue vacuuming, or perform other functions to ensure trouble-free docking. These operations may occur when the robot 40 detects the avoidance signal 60, thus recognizing that it is close to the base station 10, or at some other predetermined time, e.g., upon a change in the signal from the emitters 62, 64.


Various methods are contemplated for ensuring that the robot 40 correctly docks with base station 10. For example, the robot 40 can continue to move toward the base station 10 (within the yellow zone 66) until the bumper 48 is depressed, signaling the robot 40 that it has contacted the base station 10. Another embodiment overlaps the homing signals 62, 64 such that the yellow zone 66 terminates at a point calibrated such that the robot 40 will contact the charging contacts 16 upon reaching the termination point. Other embodiments simply stop the robot 40 when its electrical contacts touch the electrical contacts 16 on the base station 10. This would guarantee that the robot 40 is moving over the contacts 16, providing a wiping action that cleans the contacts 16 and improves the electrical integrity of the connection. This also enables the base station 10 to be lighter, since it does not have to resist the force necessary to depress the robot's bumper 48. FIG. 5 shows the robotic device 40 completely docked with the base station 10. Naturally, this procedure may also utilize detector 52 or a combination of both detectors.


While this embodiment of the invention describes use of IR signals for both avoidance and homing, the system and method of the present invention can use other signals to accomplish the goals. Other types of waves may have drawbacks, however. For example, radio waves are more difficult and expensive to make directional, and visible light suffers from interference from many sources and may be distracting to users. Sound waves could also be used, but it is similarly difficult to make sound purely directional and such waves tend to scatter and reflect more.



FIG. 7 depicts a schematic diagram which shows the control sequence 200 of the robotic device 40 during vacuuming. Generally, the control sequence 200 includes three sub-sequences based on the measured energy level of the robotic device 40. Those are referenced generally as a high energy level 210, a medium energy level 220, and a low energy level 230. In the high energy level subsequence 210, the robotic device 40 performs its predetermined task, in this case, vacuuming (utilizing various behavioral modes as described above), while avoiding the base station 212. When avoiding the base station 212, the robotic device 40 performs its avoidance behavior and continues to operate normally. This process continues while the robotic device 40 continually monitors its energy level 214. Various methods are available to monitor the energy level 214 of the power source, such as coulometry (i.e., the measuring of current constantly entering and leaving the power source), or simply measuring voltage remaining in the power source. Other embodiments of the robotic device 40 may simply employ a timer and a look-up table stored in memory to determine how long the robotic device 40 can operate before it enters a different energy level subsequence. Still other embodiments may simply operate the robot 40 for a predetermined time period before recharging, without determining which energy level subsequence it is operating in. If the robot 40 operates on a liquid or gaseous fuel, this level may also be measured with devices currently known in the art.


Once the energy remaining drops below a predetermined high level, the robot 40 enters its medium energy level sequence 220. The robot 40 continues to vacuum and monitor its energy level 224, employing methods indicated in step 214 above. In the medium energy level 220, however, the robot 40 “passively seeks” 222 the base station 10. While passively seeking 222 the base station 10, the robot 40 does not alter its travel characteristics; rather, it continues about its normal behavioral mode until it fortuitously detects the avoidance signal 60 or a homing signal 62, 64, each of which may be followed until the robot 40 ultimately docks with the base station 10. In other words, if the robot detects the avoidance signal 60 while passively seeking 222, rather than avoiding the base station 10 as it normally would, it alters its travel characteristics until it detects the homing signals 62 or 64, thus allowing it to dock.


Alternatively, the robot 40 continues operating in this medium energy level subsequence 220 until it registers an energy level 224 below a predetermined low level. At this point, the robot 40 enters the low level subsequence 230, characterized by a change in operation and travel characteristics. To conserve energy, the robot 40 may discontinue powering all incidental systems, and operations, such as vacuuming, allowing it to conserve as much energy as possible for “actively searching” 232 for the base station 10. While actively searching 232, the robot 40 may alter its travel characteristics to increase its chances of finding the base station 10. It may discontinue behavioral modes such as those employing a spiral movement, which do not necessarily create a higher chance of locating the base station, in favor of more deliberate modes, such as wall-following. This deliberate seeking will continue until the robot 40 detects the presence of the base station 10, either by detecting the avoidance signal 60 or the homing signals 62, 64. Clearly, additional subsequences may be incorporated which sound alarms when the power remaining reaches a critical level, or which reconstruct the route the robot 40 has taken since last contacting the base station 10 to aid in relocating the station 10.


The robot 40 may also dock because it has determined that it has completed its assigned task (e.g., vacuuming a room). The robot 40 may make this determination based on a variety of factors, including considerations regarding room size, total run time, total distance traveled, dirt sensing, etc. Alternatively, the robot may employ room-mapping programs, using the base station 10 and/or walls and large objects as points of reference. Upon determining that it has completed its task, the robot 40 will alter its travel characteristics in order to find the base station 10 quickly.


Once the robot 40 contacts the base station 10, it can recharge itself autonomously. Circuitry within the base station 10 detects the presence of the robot 40 and then switches on the charging voltage to its contacts 16. The robot 40 then detects the presence of the charging voltage and then switches on its internal transistor power switch to allow current flow into the battery. In one embodiment, the base station 10 contains a constant-current type switching charger. Maximum current is limited to approximately 1.25 amps even under a short circuit condition. Maximum unloaded terminal voltage is limited to approximately 22Vdc. This constant-current charging circuit is used to charge the battery in the robot 40 via the electrical connections provided by the contacts 16 on the base station 10 and those on the undercarriage 54 of the robot 40. One embodiment of this charging sequence is detailed below.


Generally, while the robot 40 is away from the base station 10, the charging contacts 16 will present five volts, limited to 1 mA maximum short circuit current flow. This low voltage/low current “sense” condition limits the amount of available energy at the contacts 16, thus rendering them safe in the event they are contacted by humans, animals, and electrically conductive objects. The contacts on the undercarriage 54 of the robot 40, when contacting the contacts 16 on the base station 10, present a precise resistive load that, along with a resistor in the base station 10, creates a high impedance voltage divider. A microprocessor that constantly monitors the voltage across the contacts 16 recognizes this lower voltage. This voltage divider creates a specific voltage, plus or minus a known tolerance. When the microprocessor determines that the voltage has fallen into the specific range, it detects that the robot 40 is present. The microprocessor then turns on a transistor switch that delivers a higher voltage/current charge (capable of charging the robot's internal battery) to the charging contacts 16. Alternatively, the robot 40 and/or base station 10 can verify the integrity of the charging circuit by sending signals through the IR beams, thereby confirming that the robot 40 has, in fact, docked.



FIG. 8 depicts an embodiment of the charger circuitry schematic. With five volts being presented by the base station, it is the job of resistor dividers R101 and R116 to hold Q48 and Q5 off when J25 is in contact with the initial low voltage state. This divider also provides the known impedance of R101 plus R116 in parallel with R224 plus the base-emitter diode drop of Q48. This Thevenin impedance is in series with a resistor in the docking station thus forming a voltage divider. A window comparator circuit within the docking station looks for a specific voltage created by the divider. Once the base station has determined this impedance is likely the robot (not some other conductive body), it then delivers the full 22 volt capable, 1.25 Amp charging voltage to the robot.


At the onset of this higher voltage, the divider of R101 and R224 are such that the requirements are met to turn on Q48 and Q5 respectively. It is this combination of transistors that then allows current to flow to the on-board robot electronics only, allowing the robot's processor to become active if in fact it was inoperative due to a depleted battery.


Once operative, the robot's processor is then able to detect the presence of the base station voltage via R113 and D15 and if driving, turn off its drive motors. Once stable on the charging contacts, it becomes the job of the robot processor to measure the internal robot battery and decide when and what type of charging control cycle is needed when allowing current to flow into the battery. For example, if the battery is at 12 volts, then it is acceptable to turn on Q45 and Q47 via processor control, in order to allow current to flow through FET U9 to the battery on a continuous basis.


If, however, the battery voltage is deemed less than 5 volts, it generally would not be desirable to allow the full current to flow to the battery on a continuous basis. The reason this condition is of concern lies in the fact that the power source within the DOC is a constant current charger, which will adjust its output voltage to be slightly higher than the battery voltage in order to flow 1.25 A into the battery. In some cases, this might be millivolts higher than the battery voltage itself and in the case of the battery at low voltage, for example, 3 volts, would cause the output voltage to drop below the necessary 5 volt level needed to operate the on board base station and robot electronics suite.


In this case, the robot processor then delivers a pulse width modulation to the charger control line pertaining to Q47, such that the energy storage capacitors in both the robot and base station maintain enough charge to keep their respective electronics working properly throughout the charge pulse. The energy storage capacitors are then replenished during the off time of the pulse width modulation charging cycle, ready to then sustain the next charge pulse. This scenario continues until the battery has been charged to the point where a continuous charge is no longer able to bring the supply voltage down to a critical level and the charge control can become a static level.


Since this pulse width modulation process in this embodiment relies on software control, health monitoring of the processor, both within the base station and robot, are important. The requirement then set fourth for charging is for a charger “watchdog” be incorporated via Q45 such that a static high or low state on this signal line will disable current flow into the battery. It is a requirement of the robot processor to continuously pulse this control line in order for any current to flow, therefore eliminating most cases of processor latch up due to electrostatic discharge or other battery related events from mistreating the charging profile. Naturally, other control and related fail safe schemes could be utilized.


The described charging sequence provides particular safety features, even though the charging contacts 16 are exposed and energized. Because a specific resistance is required to create a specific voltage drop across the contacts 16 when the 5-volt sense voltage is present (i.e., when the robot 40 is not docked) there is no danger of electric shock due to accidental contact because the low sense current is harmless. Also, the base station 10 will never switch to the higher voltage/current level, because the sense current has not entered the predetermined range. When the base station 10 does determine that the robot 40 is present, it delivers the charging voltage/current. This charging current is limited to approximately 22 volts/1.25 amps maximum. Even if inadvertent contact occurred during delivery of the charging current—which is unlikely, since the robot chassis 44 effectively blocks the contacts 16—the voltage delivered would not present a serious shock hazard, as it is relatively low.


Another level of safety is afforded by the base station 10 checking for the robot 40 at regular intervals, from as little as once per minute to as much as 10 times per second or more. Thus, in the event that the robot 40 is dislodged from the base station 10 (either by an animal or human), the charging current could be shut down immediately. This same condition applies if the contacts 16 are short circuited with the robot 40 docked (either intentionally or accidentally, for example, if the robot 40 drags debris onto the charging contacts 16).


An additional safety feature of this charging sequence prevents overheating of contacts 16 due to intentional shorting or oxidation. A thermal circuit breaker or similar device can be employed to perform this task, as well as a microprocessor equipped with a temperature measuring subroutine. The circuit breaker, however, provides the advantage of controlling contact temperature in the event of a microprocessor or software failure. Additionally, the base station 10 circuitry can also incorporate a timer to reset the temperature measuring subroutine or circuit breaker in the event of system failure. These safety controls may be incorporated into the “watchdog” described above.


While docked with the base station 10, the robot 40 can also perform other maintenance or diagnostic checks. In certain embodiments, the robot 40 can completely recharge its power source or only partially charge it, based on various factors. For example, if the robot 40 determines, through the use of route-tracking subroutines, that only a small portion of the room still requires vacuuming, it may take only a minimal charge before returning to complete cleaning of the room. If, however, the robot 40 requires a full charge before returning to clean the room, that option is also available. If the robot 40 has completed its vacuuming of the room prior to docking, it may dock, fully recharge, and stand by to await a signal (either internal or external) to begin its next cleaning cycle. While in this stand-by mode, the robot 40 may continue to measure its energy levels and may begin charging sequences upon reaching an energy level below a predetermined amount. Alternatively, the robot 40 may maintain a constant or near-constant trickle charge to keep its energy levels at or near peak. Other behaviors while in the docking position such as diagnostic functions, internal mechanism cleaning, communication with a network, or data manipulation functions may also be performed.


While there have been described herein what are to be considered exemplary and preferred embodiments of the present invention, other modifications of the invention will become apparent to those skilled in the art from the teachings herein. The particular methods of manufacture and geometries disclosed herein are exemplary in nature and are not to be considered limiting. It is therefore desired to be secured in the appended claims all such modifications as fall within the spirit and scope of the invention. Accordingly, what is desired to be secured by Letters Patent is the invention as defined and differentiated in the following claims.

Claims
  • 1. A system for charging an autonomous robot, the system comprising: an autonomous mobile device comprising an undercarriage,a wheel extending from the undercarriage toward a ground surface to support at least a portion of the mobile device above the ground surface, anda detector vertically aligned with the wheel and disposed above the wheel; anda stationary charger comprising a base plate defining a wheel receiver configured to receive the wheel of the autonomous mobile device, the wheel receiver comprising a depression in the base plate,charging contacts disposed along the base plate, wherein: the charging contacts are configured to align with corresponding charging contacts on the undercarriage of the autonomous mobile device when the wheel of the autonomous mobile device is disposed in the wheel receiver;the wheel of the autonomous mobile device is positionable in the wheel receiver defined by the depression in the base plate to establish electrical communication between the autonomous mobile device and the stationary charger, andthe depression in the base plate forming the wheel receiver is at least partially between the charging contacts and the contacts are elevated relative to the wheel receiver.
  • 2. The system of claim 1, wherein the wheel and the detector are each disposed along a forward portion of the mobile device.
  • 3. The system of claim 1, wherein the wheel receiver defines a substantially oval shape having a first diameter and a second diameter, the first diameter greater than the second diameter, and the charging contacts separated from one another by a distance greater than the first diameter.
  • 4. The system of claim 1, wherein the charging contacts are symmetrically disposed on either side of the wheel receiver.
  • 5. The system of claim 1, wherein the charging contacts extend above the base plate.
  • 6. The system of claim 5, wherein the charging contacts are each compliant with respect to the base plate.
  • 7. The system of claim 5, wherein the charging contacts are dome shaped.
  • 8. The system of claim 1, wherein the charging contacts comprise a positive charging contact and a negative charging contact.
  • 9. The system of claim 1, wherein an angle defined between the base plate and the ground surface is 0 degrees to about 20 degrees.
  • 10. The system of claim 1, wherein the stationary charger further comprises a backstop substantially vertical to the base plate.
  • 11. The system of claim 10, wherein the mobile device further comprises a displaceable bumper carried on a forward portion of the mobile device, the displaceable bumper positionable against backstop.
  • 12. The system of claim 11, wherein the backstop defines a concave surface, and at least a portion of the displaceable bumper is positionable along the concave surface of the backstop.
  • 13. The system of claim 1, wherein the stationary charger further comprises a signal emitter configured to be substantially axially aligned with the wheel of the autonomous mobile device when the wheel of the autonomous mobile device is disposed in the wheel receiver with electrical communication established between the detector of the autonomous mobile device and the stationary charger.
  • 14. A system for charging an autonomous robot, the system comprising: an autonomous mobile device comprising an undercarriage,a wheel extending from the undercarriage toward a ground surface to support at least a portion of the mobile device above the ground surface, anda detector vertically aligned with the wheel and disposed above the wheel; anda stationary charger comprisinga base plate defining a wheel receiver configured to receive the wheel of the autonomous mobile device,charging contacts disposed along the base plate, wherein the charging contacts align with corresponding charging contacts on the undercarriage of the autonomous mobile device and the wheel of the autonomous mobile device is positionable in the wheel receiver defined by the base plate to establish electrical communication between the autonomous mobile device and the stationary charger, and wherein the wheel receiver is defined by a portion of the base plate between the charging contacts and has a substantially oval shape having a first diameter and a second diameter, the first diameter greater than the second diameter, and the charging contacts separated from one another by a distance greater than the first diameter and are symmetrically disposed on either side of the wheel receiver, anda signal emitter substantially axially aligned with the wheel of the autonomous mobile device disposed in the wheel receiver with electrical communication established between the detector of the autonomous mobile device and the stationary charger.
  • 15. The system of claim 14, wherein the charging contacts extend above the base plate.
  • 16. The system of claim 15, wherein the charging contacts are each compliant with respect to the base plate.
  • 17. The system of claim 15, wherein the charging contacts are dome shaped.
  • 18. The system of claim 14, wherein an angle defined between the base plate and the ground surface is 0 degrees to about 20 degrees.
  • 19. The system of claim 14, wherein the stationary charger further comprises a backstop substantially vertical to the base plate.
Parent Case Info

This application is a continuation of, and claims priority under 35 U.S.C. §120 from, U.S. application Ser. No. 11/648,230, entitled “Autonomous Robot Auto-Docking and Energy Management Systems and Methods,” filed on Dec. 29, 2006, which is a divisional, and claims priority under 35 U.S.C. §120 from, U.S. application Ser. No. 10/762,219, entitled “Autonomous Robot Auto-Docking and Energy Management Systems and Methods,” filed on Jan. 21, 2004 now U.S. Pat. No. 7,332,890. The disclosures of each of these prior applications are considered part of the disclosure of this application and are hereby incorporated by reference in their entireties.

US Referenced Citations (893)
Number Name Date Kind
1755054 Darst Apr 1930 A
1780221 Buchmann Nov 1930 A
1970302 Gerhardt Aug 1934 A
2136324 John Nov 1938 A
2302111 Dow et al. Nov 1942 A
2353621 Sav et al. Jul 1944 A
2770825 Pullen Nov 1956 A
3119369 Harland et al. Jan 1964 A
3166138 Dunn Jan 1965 A
3333564 Waters Aug 1967 A
3375375 Robert et al. Mar 1968 A
3381652 Schaefer et al. May 1968 A
3457575 Bienek Jul 1969 A
3550714 Bellinger Dec 1970 A
3569727 Aggarwal et al. Mar 1971 A
3674316 De Jul 1972 A
3678882 Kinsella Jul 1972 A
3744586 Leinauer Jul 1973 A
3756667 Bombardier et al. Sep 1973 A
3809004 Leonheart May 1974 A
3816004 Bignardi Jun 1974 A
3845831 James Nov 1974 A
RE28268 Autrand Dec 1974 E
3853086 Asplund Dec 1974 A
3863285 Hukuba Feb 1975 A
3888181 Kups Jun 1975 A
3937174 Haaga Feb 1976 A
3952361 Wilkins Apr 1976 A
3989311 Debrey Nov 1976 A
3989931 Phillips Nov 1976 A
4004313 Capra Jan 1977 A
4012681 Finger et al. Mar 1977 A
4070170 Leinfelt Jan 1978 A
4099284 Shinozaki et al. Jul 1978 A
4119900 Kremnitz Oct 1978 A
4175589 Nakamura et al. Nov 1979 A
4175892 De Nov 1979 A
4196727 Verkaart et al. Apr 1980 A
4198727 Farmer Apr 1980 A
4199838 Simonsson Apr 1980 A
4209254 Reymond et al. Jun 1980 A
D258901 Keyworth Apr 1981 S
4297578 Carter Oct 1981 A
4306329 Yokoi Dec 1981 A
4309758 Halsall et al. Jan 1982 A
4328545 Halsall et al. May 1982 A
4367403 Miller Jan 1983 A
4369543 Chen et al. Jan 1983 A
4401909 Gorsek Aug 1983 A
4416033 Specht Nov 1983 A
4445245 Lu May 1984 A
4465370 Yuasa et al. Aug 1984 A
4477998 You Oct 1984 A
4481692 Kurz Nov 1984 A
4482960 Pryor Nov 1984 A
4492058 Goldfarb et al. Jan 1985 A
4513469 Godfrey et al. Apr 1985 A
D278732 Ohkado May 1985 S
4518437 Sommer May 1985 A
4534637 Suzuki et al. Aug 1985 A
4556313 Miller et al. Dec 1985 A
4575211 Matsumura et al. Mar 1986 A
4580311 Kurz Apr 1986 A
4601082 Kurz Jul 1986 A
4618213 Chen Oct 1986 A
4620285 Perdue Oct 1986 A
4624026 Olson et al. Nov 1986 A
4626995 Lofgren et al. Dec 1986 A
4628454 Ito Dec 1986 A
4638445 Mattaboni Jan 1987 A
4644156 Takahashi et al. Feb 1987 A
4649504 Krouglicof et al. Mar 1987 A
4652917 Miller Mar 1987 A
4654492 Koerner et al. Mar 1987 A
4654924 Getz et al. Apr 1987 A
4660969 Sorimachi et al. Apr 1987 A
4662854 Fang May 1987 A
4674048 Okumura Jun 1987 A
4679152 Perdue Jul 1987 A
4680827 Hummel Jul 1987 A
4696074 Cavalli et al. Sep 1987 A
D292223 Trumbull Oct 1987 S
4700301 Dyke Oct 1987 A
4700427 Knepper Oct 1987 A
4703820 Reinaud Nov 1987 A
4710020 Maddox et al. Dec 1987 A
4716621 Zoni Jan 1988 A
4728801 O'Connor Mar 1988 A
4733343 Yoneda et al. Mar 1988 A
4733430 Westergren Mar 1988 A
4733431 Martin Mar 1988 A
4735136 Lee et al. Apr 1988 A
4735138 Gawler et al. Apr 1988 A
4748336 Fujie et al. May 1988 A
4748833 Nagasawa Jun 1988 A
4756049 Uehara Jul 1988 A
4767213 Hummel Aug 1988 A
4769700 Pryor Sep 1988 A
4777416 George, II et al. Oct 1988 A
D298766 Tanno et al. Nov 1988 S
4782550 Jacobs Nov 1988 A
4796198 Boultinghouse et al. Jan 1989 A
4806751 Abe et al. Feb 1989 A
4811228 Hyyppa Mar 1989 A
4813906 Matsuyama et al. Mar 1989 A
4815157 Tsuchiya Mar 1989 A
4817000 Eberhardt Mar 1989 A
4818875 Weiner Apr 1989 A
4829442 Kadonoff et al. May 1989 A
4829626 Harkonen et al. May 1989 A
4832098 Palinkas et al. May 1989 A
4851661 Everett Jul 1989 A
4854000 Takimoto Aug 1989 A
4854006 Nishimura et al. Aug 1989 A
4855915 Dallaire Aug 1989 A
4857912 Everett et al. Aug 1989 A
4858132 Holmquist Aug 1989 A
4867570 Sorimachi et al. Sep 1989 A
4880474 Koharagi et al. Nov 1989 A
4887415 Martin Dec 1989 A
4891762 Chotiros Jan 1990 A
4893025 Lee Jan 1990 A
4901394 Nakamura et al. Feb 1990 A
4905151 Weiman et al. Feb 1990 A
4912643 Beirne Mar 1990 A
4918441 Bohman Apr 1990 A
4919224 Shyu et al. Apr 1990 A
4919489 Kopsco Apr 1990 A
4920060 Parrent et al. Apr 1990 A
4920605 Takashima May 1990 A
4933864 Evans et al. Jun 1990 A
4937912 Kurz Jul 1990 A
4953253 Fukuda et al. Sep 1990 A
4954962 Evans et al. Sep 1990 A
4955714 Stotler et al. Sep 1990 A
4956891 Wulff Sep 1990 A
4961303 McCarty et al. Oct 1990 A
4961304 Ovsborn et al. Oct 1990 A
4962453 Pong et al. Oct 1990 A
4971591 Raviv et al. Nov 1990 A
4973912 Kaminski et al. Nov 1990 A
4974283 Holsten et al. Dec 1990 A
4977618 Allen Dec 1990 A
4977639 Takahashi et al. Dec 1990 A
4986663 Cecchi et al. Jan 1991 A
5001635 Yasutomi et al. Mar 1991 A
5002145 Wakaumi et al. Mar 1991 A
5012886 Jonas et al. May 1991 A
5018240 Holman May 1991 A
5020186 Lessig et al. Jun 1991 A
5022812 Coughlan et al. Jun 1991 A
5023788 Kitazume et al. Jun 1991 A
5024529 Svetkoff et al. Jun 1991 A
D318500 Malewicki et al. Jul 1991 S
5032775 Mizuno et al. Jul 1991 A
5033151 Kraft et al. Jul 1991 A
5033291 Podoloff et al. Jul 1991 A
5040116 Evans et al. Aug 1991 A
5045769 Everett, Jr. Sep 1991 A
5049802 Mintus et al. Sep 1991 A
5051906 Evans et al. Sep 1991 A
5062819 Mallory Nov 1991 A
5070567 Holland Dec 1991 A
5084934 Lessig et al. Feb 1992 A
5086535 Grossmeyer et al. Feb 1992 A
5090321 Abouav Feb 1992 A
5093955 Blehert et al. Mar 1992 A
5094311 Akeel Mar 1992 A
5105502 Takashima Apr 1992 A
5105550 Shenoha Apr 1992 A
5109566 Kobayashi et al. May 1992 A
5115538 Cochran et al. May 1992 A
5127128 Lee Jul 1992 A
5136675 Hodson Aug 1992 A
5136750 Takashima et al. Aug 1992 A
5142985 Stearns et al. Sep 1992 A
5144471 Takanashi et al. Sep 1992 A
5144714 Mori et al. Sep 1992 A
5144715 Matsuyo et al. Sep 1992 A
5152028 Hirano Oct 1992 A
5152202 Strauss Oct 1992 A
5155684 Burke et al. Oct 1992 A
5163202 Kawakami et al. Nov 1992 A
5163320 Goshima et al. Nov 1992 A
5164579 Pryor et al. Nov 1992 A
5165064 Mattaboni Nov 1992 A
5170352 McTamaney et al. Dec 1992 A
5173881 Sindle Dec 1992 A
5182833 Yamaguchi et al. Feb 1993 A
5202742 Frank et al. Apr 1993 A
5204814 Noonan et al. Apr 1993 A
5206500 Decker et al. Apr 1993 A
5208521 Aoyama May 1993 A
5216777 Moro et al. Jun 1993 A
5227985 DeMenthon Jul 1993 A
5233682 Abe et al. Aug 1993 A
5239720 Wood et al. Aug 1993 A
5251358 Moro et al. Oct 1993 A
5261139 Lewis Nov 1993 A
5276618 Everett Jan 1994 A
5276939 Uenishi Jan 1994 A
5277064 Knigga et al. Jan 1994 A
5279672 Betker et al. Jan 1994 A
5284452 Corona Feb 1994 A
5284522 Kobayashi et al. Feb 1994 A
5293955 Lee Mar 1994 A
D345707 Alister Apr 1994 S
5303448 Hennessey et al. Apr 1994 A
5307273 Oh et al. Apr 1994 A
5309592 Hiratsuka May 1994 A
5310379 Hippely et al. May 1994 A
5315227 Pierson et al. May 1994 A
5319827 Yang Jun 1994 A
5319828 Waldhauser et al. Jun 1994 A
5321614 Ashworth Jun 1994 A
5323483 Baeg Jun 1994 A
5324948 Dudar et al. Jun 1994 A
5341186 Kato Aug 1994 A
5341540 Soupert et al. Aug 1994 A
5341549 Wirtz et al. Aug 1994 A
5345649 Whitlow Sep 1994 A
5353224 Lee et al. Oct 1994 A
5363305 Cox et al. Nov 1994 A
5363935 Schempf et al. Nov 1994 A
5369347 Yoo Nov 1994 A
5369838 Wood et al. Dec 1994 A
5386862 Glover et al. Feb 1995 A
5399951 Lavallee et al. Mar 1995 A
5400244 Watanabe et al. Mar 1995 A
5404612 Ishikawa Apr 1995 A
5410479 Coker Apr 1995 A
5435405 Schempf et al. Jul 1995 A
5440216 Kim Aug 1995 A
5442358 Keeler et al. Aug 1995 A
5444965 Colens Aug 1995 A
5446356 Kim Aug 1995 A
5446445 Bloomfield et al. Aug 1995 A
5451135 Schempf et al. Sep 1995 A
5454129 Kell Oct 1995 A
5455982 Armstrong et al. Oct 1995 A
5465525 Mifune et al. Nov 1995 A
5465619 Sotack et al. Nov 1995 A
5467273 Faibish et al. Nov 1995 A
5471560 Allard et al. Nov 1995 A
5491670 Weber Feb 1996 A
5497529 Boesi Mar 1996 A
5498948 Bruni et al. Mar 1996 A
5502638 Takenaka Mar 1996 A
5505072 Oreper Apr 1996 A
5507067 Hoekstra et al. Apr 1996 A
5510893 Suzuki Apr 1996 A
5511147 Abdel Apr 1996 A
5515572 Hoekstra et al. May 1996 A
5534762 Kim Jul 1996 A
5537017 Feiten et al. Jul 1996 A
5537711 Tseng Jul 1996 A
5539953 Kurz Jul 1996 A
5542146 Hoekstra et al. Aug 1996 A
5542148 Young Aug 1996 A
5546631 Chambon Aug 1996 A
5548511 Bancroft Aug 1996 A
5551525 Pack et al. Sep 1996 A
5553349 Kilstrom et al. Sep 1996 A
5555587 Guha Sep 1996 A
5560077 Crotchett Oct 1996 A
5568589 Hwang Oct 1996 A
D375592 Ljunggren Nov 1996 S
5608306 Rybeck et al. Mar 1997 A
5608894 Kawakami et al. Mar 1997 A
5608944 Gordon Mar 1997 A
5610488 Miyazawa Mar 1997 A
5611106 Wulff Mar 1997 A
5611108 Knowlton et al. Mar 1997 A
5613261 Kawakami et al. Mar 1997 A
5613269 Miwa Mar 1997 A
5621291 Lee Apr 1997 A
5622236 Azumi et al. Apr 1997 A
5634237 Paranjpe Jun 1997 A
5634239 Tuvin et al. Jun 1997 A
5636402 Kubo et al. Jun 1997 A
5642299 Hardin et al. Jun 1997 A
5646494 Han Jul 1997 A
5647554 Ikegami et al. Jul 1997 A
5650702 Azumi Jul 1997 A
5652489 Kawakami Jul 1997 A
5682313 Edlund et al. Oct 1997 A
5682839 Grimsley et al. Nov 1997 A
5696675 Nakamura et al. Dec 1997 A
5698861 Oh Dec 1997 A
5709007 Chiang Jan 1998 A
5710506 Broell et al. Jan 1998 A
5714119 Kawagoe et al. Feb 1998 A
5717169 Liang et al. Feb 1998 A
5717484 Hamaguchi et al. Feb 1998 A
5720077 Nakamura et al. Feb 1998 A
5732401 Conway Mar 1998 A
5735959 Kubo et al. Apr 1998 A
5745235 Vercammen et al. Apr 1998 A
5752871 Tsuzuki May 1998 A
5756904 Oreper et al. May 1998 A
5761762 Kubo et al. Jun 1998 A
5764888 Bolan et al. Jun 1998 A
5767437 Rogers Jun 1998 A
5767960 Orman Jun 1998 A
5777596 Herbert Jul 1998 A
5778486 Kim Jul 1998 A
5781697 Jeong Jul 1998 A
5781960 Kilstrom et al. Jul 1998 A
5786602 Pryor et al. Jul 1998 A
5787545 Colens Aug 1998 A
5793900 Nourbakhsh et al. Aug 1998 A
5794297 Muta Aug 1998 A
5812267 Everett et al. Sep 1998 A
5814808 Takada et al. Sep 1998 A
5815880 Nakanishi Oct 1998 A
5815884 Imamura et al. Oct 1998 A
5819008 Asama et al. Oct 1998 A
5819360 Fujii Oct 1998 A
5819936 Saveliev et al. Oct 1998 A
5820821 Kawagoe et al. Oct 1998 A
5821730 Drapkin Oct 1998 A
5825981 Matsuda Oct 1998 A
5828770 Leis et al. Oct 1998 A
5831597 West et al. Nov 1998 A
5839156 Park et al. Nov 1998 A
5839532 Yoshiji et al. Nov 1998 A
5841259 Kim et al. Nov 1998 A
5867800 Leif Feb 1999 A
5869910 Colens Feb 1999 A
5896611 Haaga Apr 1999 A
5903124 Kawakami May 1999 A
5905209 Oreper May 1999 A
5907886 Buscher Jun 1999 A
5910700 Crotzer Jun 1999 A
5911260 Suzuki Jun 1999 A
5916008 Wong Jun 1999 A
5924167 Wright et al. Jul 1999 A
5926909 McGee Jul 1999 A
5933102 Miller et al. Aug 1999 A
5933913 Wright et al. Aug 1999 A
5935179 Kleiner et al. Aug 1999 A
5940346 Sadowsky et al. Aug 1999 A
5940927 Haegermarck et al. Aug 1999 A
5940930 Oh et al. Aug 1999 A
5942869 Katou et al. Aug 1999 A
5943730 Boomgaarden Aug 1999 A
5943733 Tagliaferri Aug 1999 A
5947225 Kawakami et al. Sep 1999 A
5950408 Schaedler Sep 1999 A
5959423 Nakanishi et al. Sep 1999 A
5968281 Wright et al. Oct 1999 A
5974348 Rocks Oct 1999 A
5974365 Mitchell Oct 1999 A
5983448 Wright et al. Nov 1999 A
5984880 Lander et al. Nov 1999 A
5989700 Krivopal Nov 1999 A
5991951 Kubo et al. Nov 1999 A
5995883 Nishikado Nov 1999 A
5995884 Allen et al. Nov 1999 A
5996167 Close Dec 1999 A
5998953 Nakamura et al. Dec 1999 A
5998971 Corbridge Dec 1999 A
6000088 Wright et al. Dec 1999 A
6009358 Angott et al. Dec 1999 A
6021545 Delgado et al. Feb 2000 A
6023813 Thatcher et al. Feb 2000 A
6023814 Imamura Feb 2000 A
6025687 Himeda et al. Feb 2000 A
6026539 Mouw et al. Feb 2000 A
6030464 Azevedo Feb 2000 A
6030465 Marcussen et al. Feb 2000 A
6032542 Warnick et al. Mar 2000 A
6036572 Sze Mar 2000 A
6038501 Kawakami Mar 2000 A
6040669 Hog Mar 2000 A
6041471 Charkey et al. Mar 2000 A
6041472 Kasen et al. Mar 2000 A
6046800 Ohtomo et al. Apr 2000 A
6049620 Dickinson et al. Apr 2000 A
6052821 Chouly et al. Apr 2000 A
6055042 Sarangapani Apr 2000 A
6055702 Imamura et al. May 2000 A
6061868 Moritsch et al. May 2000 A
6065182 Wright et al. May 2000 A
6073432 Schaedler Jun 2000 A
6076025 Ueno et al. Jun 2000 A
6076026 Jambhekar et al. Jun 2000 A
6076226 Reed Jun 2000 A
6076227 Schallig et al. Jun 2000 A
6081257 Zeller Jun 2000 A
6088020 Mor Jul 2000 A
6094775 Behmer Aug 2000 A
6099091 Campbell Aug 2000 A
6101671 Wright et al. Aug 2000 A
6108031 King et al. Aug 2000 A
6108067 Okamoto Aug 2000 A
6108076 Hanseder Aug 2000 A
6108269 Kabel Aug 2000 A
6108597 Kirchner et al. Aug 2000 A
6112143 Allen et al. Aug 2000 A
6112996 Matsuo Sep 2000 A
6119057 Kawagoe Sep 2000 A
6122798 Kobayashi et al. Sep 2000 A
6124694 Bancroft et al. Sep 2000 A
6125498 Roberts et al. Oct 2000 A
6131237 Kasper et al. Oct 2000 A
6138063 Himeda Oct 2000 A
6142252 Kinto et al. Nov 2000 A
6146278 Kobayashi Nov 2000 A
6154279 Thayer Nov 2000 A
6154694 Aoki et al. Nov 2000 A
6160479 Åhle'n et al. Dec 2000 A
6167332 Kurtzberg et al. Dec 2000 A
6167587 Kasper et al. Jan 2001 B1
6192548 Huffman Feb 2001 B1
6216307 Kaleta et al. Apr 2001 B1
6220865 Macri et al. Apr 2001 B1
6226830 Hendriks et al. May 2001 B1
6230362 Kasper et al. May 2001 B1
6237741 Guidetti May 2001 B1
6240342 Fiegert et al. May 2001 B1
6243913 Frank et al. Jun 2001 B1
6255793 Peless et al. Jul 2001 B1
6259979 Holmquist Jul 2001 B1
6261379 Conrad et al. Jul 2001 B1
6263539 Baig Jul 2001 B1
6263989 Won Jul 2001 B1
6272936 Oreper et al. Aug 2001 B1
6276478 Hopkins et al. Aug 2001 B1
6278918 Dickson et al. Aug 2001 B1
6282526 Ganesh Aug 2001 B1
6283034 Miles Sep 2001 B1
6285778 Nakajima et al. Sep 2001 B1
6285930 Dickson et al. Sep 2001 B1
6300737 Bergvall et al. Oct 2001 B1
6321337 Reshef et al. Nov 2001 B1
6321515 Colens Nov 2001 B1
6323570 Nishimura et al. Nov 2001 B1
6324714 Walz et al. Dec 2001 B1
6327741 Reed Dec 2001 B1
6332400 Meyer Dec 2001 B1
6339735 Peless et al. Jan 2002 B1
6362875 Burkley Mar 2002 B1
6370453 Sommer Apr 2002 B2
6374155 Wallach et al. Apr 2002 B1
6374157 Takamura Apr 2002 B1
6381802 Park May 2002 B2
6385515 Dickson et al. May 2002 B1
6388013 Saraf et al. May 2002 B1
6389329 Colens May 2002 B1
6400048 Nishimura et al. Jun 2002 B1
6401294 Kasper Jun 2002 B2
6408226 Byrne et al. Jun 2002 B1
6412141 Kasper et al. Jul 2002 B2
6415203 Inoue et al. Jul 2002 B1
6421870 Basham et al. Jul 2002 B1
6427285 Legatt et al. Aug 2002 B1
6430471 Kintou et al. Aug 2002 B1
6431296 Won Aug 2002 B1
6437227 Theimer Aug 2002 B1
6437465 Nishimura et al. Aug 2002 B1
6438456 Feddema et al. Aug 2002 B1
6438793 Miner et al. Aug 2002 B1
6442476 Poropat Aug 2002 B1
6443509 Levin et al. Sep 2002 B1
6444003 Sutcliffe Sep 2002 B1
6446302 Kasper et al. Sep 2002 B1
6454036 Airey et al. Sep 2002 B1
D464091 Christianson Oct 2002 S
6457206 Judson Oct 2002 B1
6459955 Bartsch et al. Oct 2002 B1
6463368 Feiten et al. Oct 2002 B1
6465982 Bergvall et al. Oct 2002 B1
6473167 Odell Oct 2002 B1
6480762 Uchikubo et al. Nov 2002 B1
6481515 Kirkpatrick et al. Nov 2002 B1
6490539 Dickson et al. Dec 2002 B1
6491127 Holmberg et al. Dec 2002 B1
6493612 Bisset et al. Dec 2002 B1
6493613 Peless et al. Dec 2002 B2
6496754 Song et al. Dec 2002 B2
6496755 Wallach et al. Dec 2002 B2
6502657 Kerrebrock et al. Jan 2003 B2
6504610 Bauer et al. Jan 2003 B1
6507773 Parker et al. Jan 2003 B2
6525509 Petersson et al. Feb 2003 B1
D471243 Cioffi et al. Mar 2003 S
6532404 Colens Mar 2003 B2
6535793 Allard Mar 2003 B2
6540607 Mokris et al. Apr 2003 B2
6548982 Papanikolopoulos et al. Apr 2003 B1
6553612 Dyson et al. Apr 2003 B1
6556722 Russell et al. Apr 2003 B1
6556892 Kuroki et al. Apr 2003 B2
6557104 Vu et al. Apr 2003 B2
D474312 Stephens et al. May 2003 S
6563130 Dworkowski et al. May 2003 B2
6571415 Gerber et al. Jun 2003 B2
6571422 Gordon et al. Jun 2003 B1
6572711 Sclafani et al. Jun 2003 B2
6574536 Kawagoe et al. Jun 2003 B1
6580246 Jacobs Jun 2003 B2
6584376 Van Kommer Jun 2003 B1
6586908 Petersson et al. Jul 2003 B2
6587573 Stam et al. Jul 2003 B1
6590222 Bisset et al. Jul 2003 B1
6594551 McKinney et al. Jul 2003 B2
6594844 Jones Jul 2003 B2
D478884 Slipy et al. Aug 2003 S
6601265 Burlington Aug 2003 B1
6604021 Imai et al. Aug 2003 B2
6604022 Parker et al. Aug 2003 B2
6605156 Clark et al. Aug 2003 B1
6611120 Song et al. Aug 2003 B2
6611734 Parker et al. Aug 2003 B2
6611738 Raffner Aug 2003 B2
6615108 Peless et al. Sep 2003 B1
6615885 Ohm Sep 2003 B1
6622465 Jerome et al. Sep 2003 B2
6624744 Wilson et al. Sep 2003 B1
6625843 Kim et al. Sep 2003 B2
6629028 Paromtchik et al. Sep 2003 B2
6639659 Granger Oct 2003 B2
6658325 Zweig Dec 2003 B2
6658354 Lin Dec 2003 B2
6658692 Lenkiewicz et al. Dec 2003 B2
6658693 Reed, Jr. Dec 2003 B1
6661239 Ozick Dec 2003 B1
6662889 De Fazio et al. Dec 2003 B2
6668951 Won Dec 2003 B2
6670817 Fournier et al. Dec 2003 B2
6671592 Bisset et al. Dec 2003 B1
6687571 Byrne et al. Feb 2004 B1
6690134 Jones et al. Feb 2004 B1
6690993 Foulke et al. Feb 2004 B2
6697147 Ko et al. Feb 2004 B2
6711280 Stafsudd et al. Mar 2004 B2
6732826 Song et al. May 2004 B2
6737591 Lapstun et al. May 2004 B1
6741054 Koselka et al. May 2004 B2
6741364 Lange et al. May 2004 B2
6748297 Song et al. Jun 2004 B2
6756703 Chang Jun 2004 B2
6760647 Nourbakhsh et al. Jul 2004 B2
6764373 Osawa et al. Jul 2004 B1
6769004 Barrett Jul 2004 B2
6774596 Bisset Aug 2004 B1
6779380 Nieuwkamp Aug 2004 B1
6781338 Jones et al. Aug 2004 B2
6809490 Jones et al. Oct 2004 B2
6810305 Kirkpatrick Oct 2004 B2
6830120 Yashima et al. Dec 2004 B1
6832407 Salem et al. Dec 2004 B2
6836701 McKee Dec 2004 B2
6841963 Song et al. Jan 2005 B2
6845297 Allard Jan 2005 B2
6856811 Burdue et al. Feb 2005 B2
6859010 Jeon et al. Feb 2005 B2
6859682 Naka et al. Feb 2005 B2
6860206 Rudakevych et al. Mar 2005 B1
6865447 Lau et al. Mar 2005 B2
6870792 Chiappetta Mar 2005 B2
6871115 Huang et al. Mar 2005 B2
6883201 Jones et al. Apr 2005 B2
6886651 Slocum et al. May 2005 B1
6888333 Laby May 2005 B2
6901624 Mori et al. Jun 2005 B2
6906702 Tanaka et al. Jun 2005 B1
6101670 Song Jul 2005 C1
6914403 Tsurumi Jul 2005 B2
6917854 Bayer Jul 2005 B2
6925679 Wallach et al. Aug 2005 B2
6929548 Wang Aug 2005 B2
D510066 Hickey et al. Sep 2005 S
6938298 Aasen Sep 2005 B2
6940291 Ozick Sep 2005 B1
6941199 Bottomley et al. Sep 2005 B1
6956348 Landry et al. Oct 2005 B2
6957712 Song et al. Oct 2005 B2
6960986 Asama et al. Nov 2005 B2
6965209 Jones et al. Nov 2005 B2
6965211 Tsurumi Nov 2005 B2
6968592 Takeuchi et al. Nov 2005 B2
6971140 Kim Dec 2005 B2
6975246 Trudeau Dec 2005 B1
6980229 Ebersole Dec 2005 B1
6985556 Shanmugavel et al. Jan 2006 B2
6993954 George et al. Feb 2006 B1
6999850 McDonald Feb 2006 B2
7013527 Thomas et al. Mar 2006 B2
7024278 Chiappetta et al. Apr 2006 B2
7024280 Parker et al. Apr 2006 B2
7027893 Perry et al. Apr 2006 B2
7030768 Wanie Apr 2006 B2
7031805 Lee et al. Apr 2006 B2
7032469 Bailey Apr 2006 B2
7053578 Diehl et al. May 2006 B2
7054716 McKee et al. May 2006 B2
5987383 Keller et al. Jun 2006 C1
7055210 Keppler et al. Jun 2006 B2
7057120 Ma et al. Jun 2006 B2
7057643 Iida et al. Jun 2006 B2
7065430 Naka et al. Jun 2006 B2
7066291 Martins et al. Jun 2006 B2
7069124 Whittaker et al. Jun 2006 B1
7079923 Abramson et al. Jul 2006 B2
7085623 Siegers Aug 2006 B2
7085624 Aldred et al. Aug 2006 B2
7113847 Chmura et al. Sep 2006 B2
7133746 Abramson et al. Nov 2006 B2
7142198 Lee Nov 2006 B2
7148458 Schell et al. Dec 2006 B2
7155308 Jones Dec 2006 B2
7167775 Abramson et al. Jan 2007 B2
7171285 Kim et al. Jan 2007 B2
7173391 Jones et al. Feb 2007 B2
7174238 Zweig Feb 2007 B1
7188000 Chiappetta et al. Mar 2007 B2
7193384 Norman et al. Mar 2007 B1
7196487 Jones et al. Mar 2007 B2
7201786 Wegelin et al. Apr 2007 B2
7206677 Hulden Apr 2007 B2
7211980 Bruemmer et al. May 2007 B1
7225500 Diehl et al. Jun 2007 B2
7246405 Yan Jul 2007 B2
7248951 Huldén Jul 2007 B2
7275280 Haegermarck et al. Oct 2007 B2
7283892 Boillot et al. Oct 2007 B1
7288912 Landry et al. Oct 2007 B2
7318248 Yan Jan 2008 B1
7320149 Huffman et al. Jan 2008 B1
7324870 Lee Jan 2008 B2
7328196 Peters Feb 2008 B2
7332890 Cohen et al. Feb 2008 B2
7352153 Yan Apr 2008 B2
7359766 Jeon et al. Apr 2008 B2
7360277 Moshenrose et al. Apr 2008 B2
7363108 Noda et al. Apr 2008 B2
7388879 Sabe et al. Jun 2008 B2
7389166 Harwig et al. Jun 2008 B2
7408157 Yan Aug 2008 B2
7418762 Arai et al. Sep 2008 B2
7430455 Casey et al. Sep 2008 B2
7430462 Chiu et al. Sep 2008 B2
7441298 Svendsen et al. Oct 2008 B2
7444206 Abramson et al. Oct 2008 B2
7448113 Jones et al. Nov 2008 B2
7459871 Landry et al. Dec 2008 B2
7467026 Sakagami et al. Dec 2008 B2
7474941 Kim et al. Jan 2009 B2
7503096 Lin Mar 2009 B2
7515991 Egawa et al. Apr 2009 B2
7555363 Augenbraun et al. Jun 2009 B2
7557703 Yamada et al. Jul 2009 B2
7568259 Yan Aug 2009 B2
7571511 Jones et al. Aug 2009 B2
7578020 Jaworski et al. Aug 2009 B2
7600521 Woo Oct 2009 B2
7603744 Reindle Oct 2009 B2
7617557 Reindle Nov 2009 B2
7620476 Morse et al. Nov 2009 B2
7636982 Jones et al. Dec 2009 B2
7647144 Haegermarck Jan 2010 B2
7650666 Jang Jan 2010 B2
7660650 Kawagoe et al. Feb 2010 B2
7663333 Jones et al. Feb 2010 B2
7693605 Park Apr 2010 B2
7706917 Chiappetta et al. Apr 2010 B1
6925357 Wang et al. May 2010 C1
7765635 Park Aug 2010 B2
7801645 Taylor et al. Sep 2010 B2
7805220 Taylor et al. Sep 2010 B2
7809944 Kawamoto Oct 2010 B2
7849555 Hahm et al. Dec 2010 B2
7853645 Brown et al. Dec 2010 B2
7920941 Park et al. Apr 2011 B2
7937800 Yan May 2011 B2
7957836 Myeong et al. Jun 2011 B2
20010004719 Sommer Jun 2001 A1
20010013929 Torsten Aug 2001 A1
20010020200 Das et al. Sep 2001 A1
20010025183 Shahidi Sep 2001 A1
20010037163 Allard Nov 2001 A1
20010043509 Green et al. Nov 2001 A1
20010045883 Holdaway et al. Nov 2001 A1
20010047231 Peless et al. Nov 2001 A1
20010047895 De et al. Dec 2001 A1
20020011367 Kolesnik Jan 2002 A1
20020011813 Koselka et al. Jan 2002 A1
20020016649 Jones Feb 2002 A1
20020021219 Edwards Feb 2002 A1
20020027652 Paromtchik et al. Mar 2002 A1
20020036779 Kiyoi et al. Mar 2002 A1
20020081937 Yamada et al. Jun 2002 A1
20020095239 Wallach et al. Jul 2002 A1
20020097400 Jung et al. Jul 2002 A1
20020104963 Mancevski Aug 2002 A1
20020108209 Peterson Aug 2002 A1
20020112742 Bredo et al. Aug 2002 A1
20020113973 Ge Aug 2002 A1
20020116089 Kirkpatrick Aug 2002 A1
20020120364 Colens Aug 2002 A1
20020124343 Reed Sep 2002 A1
20020153185 Song et al. Oct 2002 A1
20020156556 Ruffner Oct 2002 A1
20020159051 Guo Oct 2002 A1
20020166193 Kasper Nov 2002 A1
20020169521 Goodman et al. Nov 2002 A1
20020173877 Zweig Nov 2002 A1
20020189871 Won Dec 2002 A1
20030009259 Hattori et al. Jan 2003 A1
20030019071 Field et al. Jan 2003 A1
20030023356 Keable Jan 2003 A1
20030024986 Mazz et al. Feb 2003 A1
20030025472 Jones et al. Feb 2003 A1
20030028286 Glenn et al. Feb 2003 A1
20030030399 Jacobs Feb 2003 A1
20030058262 Sato et al. Mar 2003 A1
20030060928 Abramson et al. Mar 2003 A1
20030067451 Tagg et al. Apr 2003 A1
20030097875 Lentz et al. May 2003 A1
20030120389 Abramson et al. Jun 2003 A1
20030124312 Autumn Jul 2003 A1
20030126352 Barrett Jul 2003 A1
20030137268 Papanikolopoulos et al. Jul 2003 A1
20030146384 Logsdon et al. Aug 2003 A1
20030192144 Song et al. Oct 2003 A1
20030193657 Uomori et al. Oct 2003 A1
20030216834 Allard Nov 2003 A1
20030221114 Hino et al. Nov 2003 A1
20030229421 Chmura et al. Dec 2003 A1
20030229474 Suzuki et al. Dec 2003 A1
20030233171 Heiligensetzer Dec 2003 A1
20030233177 Johnson et al. Dec 2003 A1
20030233870 Mancevski Dec 2003 A1
20030233930 Ozick Dec 2003 A1
20040016077 Song et al. Jan 2004 A1
20040020000 Jones Feb 2004 A1
20040030448 Solomon Feb 2004 A1
20040030449 Solomon Feb 2004 A1
20040030450 Solomon Feb 2004 A1
20040030451 Solomon Feb 2004 A1
20040030570 Solomon Feb 2004 A1
20040030571 Solomon Feb 2004 A1
20040031113 Wosewick et al. Feb 2004 A1
20040049877 Jones et al. Mar 2004 A1
20040055163 McCambridge et al. Mar 2004 A1
20040068351 Solomon Apr 2004 A1
20040068415 Solomon Apr 2004 A1
20040068416 Solomon Apr 2004 A1
20040074038 Im et al. Apr 2004 A1
20040074044 Diehl et al. Apr 2004 A1
20040076324 Burl et al. Apr 2004 A1
20040083570 Song et al. May 2004 A1
20040085037 Jones et al. May 2004 A1
20040088079 Lavarec et al. May 2004 A1
20040093122 Galibraith May 2004 A1
20040098167 Yi et al. May 2004 A1
20040111184 Chiappetta et al. Jun 2004 A1
20040111821 Lenkiewicz et al. Jun 2004 A1
20040113777 Matsuhira et al. Jun 2004 A1
20040117064 McDonald Jun 2004 A1
20040117846 Karaoguz et al. Jun 2004 A1
20040118998 Wingett et al. Jun 2004 A1
20040128028 Miyamoto et al. Jul 2004 A1
20040133316 Dean Jul 2004 A1
20040134336 Solomon Jul 2004 A1
20040134337 Solomon Jul 2004 A1
20040143919 Wilder Jul 2004 A1
20040148419 Chen et al. Jul 2004 A1
20040148731 Damman et al. Aug 2004 A1
20040153212 Profio et al. Aug 2004 A1
20040156541 Jeon et al. Aug 2004 A1
20040158357 Lee et al. Aug 2004 A1
20040181706 Chen et al. Sep 2004 A1
20040187249 Jones et al. Sep 2004 A1
20040187457 Colens Sep 2004 A1
20040196451 Aoyama Oct 2004 A1
20040200505 Taylor et al. Oct 2004 A1
20040204792 Taylor et al. Oct 2004 A1
20040210345 Noda et al. Oct 2004 A1
20040210347 Sawada et al. Oct 2004 A1
20040211444 Taylor et al. Oct 2004 A1
20040221790 Sinclair et al. Nov 2004 A1
20040236468 Taylor et al. Nov 2004 A1
20040244138 Taylor et al. Dec 2004 A1
20040255425 Arai et al. Dec 2004 A1
20050000543 Taylor et al. Jan 2005 A1
20050010330 Abramson et al. Jan 2005 A1
20050010331 Taylor et al. Jan 2005 A1
20050021181 Kim et al. Jan 2005 A1
20050067994 Jones et al. Mar 2005 A1
20050085947 Aldred et al. Apr 2005 A1
20050137749 Jeon et al. Jun 2005 A1
20050144751 Kegg et al. Jul 2005 A1
20050150074 Diehl et al. Jul 2005 A1
20050150519 Keppler et al. Jul 2005 A1
20050154795 Kuz et al. Jul 2005 A1
20050156562 Cohen et al. Jul 2005 A1
20050165508 Kanda et al. Jul 2005 A1
20050166354 Uehigashi Aug 2005 A1
20050166355 Tani Aug 2005 A1
20050172445 Diehl et al. Aug 2005 A1
20050183229 Uehigashi Aug 2005 A1
20050183230 Uehigashi Aug 2005 A1
20050187678 Myeong et al. Aug 2005 A1
20050192707 Park et al. Sep 2005 A1
20050204717 Colens Sep 2005 A1
20050209736 Kawagoe Sep 2005 A1
20050211880 Schell et al. Sep 2005 A1
20050212929 Schell et al. Sep 2005 A1
20050213082 DiBernardo et al. Sep 2005 A1
20050213109 Schell et al. Sep 2005 A1
20050217042 Reindle Oct 2005 A1
20050218852 Landry et al. Oct 2005 A1
20050222933 Wesby Oct 2005 A1
20050229340 Sawalski et al. Oct 2005 A1
20050229355 Crouch et al. Oct 2005 A1
20050235451 Yan Oct 2005 A1
20050251292 Casey et al. Nov 2005 A1
20050255425 Pierson Nov 2005 A1
20050258154 Blankenship et al. Nov 2005 A1
20050273967 Taylor et al. Dec 2005 A1
20050288819 de Guzman Dec 2005 A1
20060000050 Cipolla et al. Jan 2006 A1
20060010638 Shimizu et al. Jan 2006 A1
20060020369 Taylor et al. Jan 2006 A1
20060020370 Abramson Jan 2006 A1
20060021168 Nishikawa Feb 2006 A1
20060025134 Cho et al. Feb 2006 A1
20060037170 Shimizu Feb 2006 A1
20060042042 Mertes et al. Mar 2006 A1
20060044546 Lewin et al. Mar 2006 A1
20060060216 Woo Mar 2006 A1
20060061657 Rew et al. Mar 2006 A1
20060064828 Stein et al. Mar 2006 A1
20060087273 Ko et al. Apr 2006 A1
20060089765 Pack et al. Apr 2006 A1
20060100741 Jung May 2006 A1
20060119839 Bertin et al. Jun 2006 A1
20060143295 Costa et al. Jun 2006 A1
20060146776 Kim Jul 2006 A1
20060190133 Konandreas et al. Aug 2006 A1
20060190146 Morse et al. Aug 2006 A1
20060196003 Song et al. Sep 2006 A1
20060220900 Ceskutti et al. Oct 2006 A1
20060259194 Chiu Nov 2006 A1
20060259494 Watson et al. Nov 2006 A1
20060288519 Jaworski et al. Dec 2006 A1
20060293787 Kanda et al. Dec 2006 A1
20070006404 Cheng et al. Jan 2007 A1
20070017061 Yan Jan 2007 A1
20070028574 Yan Feb 2007 A1
20070032904 Kawagoe et al. Feb 2007 A1
20070042716 Goodall et al. Feb 2007 A1
20070043459 Abbott et al. Feb 2007 A1
20070061041 Zweig Mar 2007 A1
20070114975 Cohen et al. May 2007 A1
20070150096 Yeh et al. Jun 2007 A1
20070157415 Lee et al. Jul 2007 A1
20070157420 Lee et al. Jul 2007 A1
20070179670 Chiappetta et al. Aug 2007 A1
20070226949 Hahm et al. Oct 2007 A1
20070234492 Svendsen et al. Oct 2007 A1
20070244610 Ozick et al. Oct 2007 A1
20070250212 Halloran et al. Oct 2007 A1
20070266508 Jones et al. Nov 2007 A1
20080007203 Cohen et al. Jan 2008 A1
20080039974 Sandin et al. Feb 2008 A1
20080052846 Kapoor et al. Mar 2008 A1
20080091304 Ozick et al. Apr 2008 A1
20080184518 Taylor Aug 2008 A1
20080276407 Schnittman et al. Nov 2008 A1
20080281470 Gilbert et al. Nov 2008 A1
20080282494 Won et al. Nov 2008 A1
20080294288 Yamauchi Nov 2008 A1
20080302586 Yan Dec 2008 A1
20080307590 Jones et al. Dec 2008 A1
20090007366 Svendsen et al. Jan 2009 A1
20090038089 Landry et al. Feb 2009 A1
20090049640 Lee et al. Feb 2009 A1
20090055022 Casey et al. Feb 2009 A1
20090102296 Greene et al. Apr 2009 A1
20090292393 Casey et al. Nov 2009 A1
20100011529 Won et al. Jan 2010 A1
20100049365 Jones et al. Feb 2010 A1
20100063628 Landry et al. Mar 2010 A1
20100107355 Won et al. May 2010 A1
20100257690 Jones et al. Oct 2010 A1
20100257691 Jones et al. Oct 2010 A1
20100263158 Jones et al. Oct 2010 A1
20100268384 Jones et al. Oct 2010 A1
20100312429 Jones et al. Dec 2010 A1
Foreign Referenced Citations (389)
Number Date Country
2003275566 Jun 2004 AU
2128842 Dec 1980 DE
3317376 Nov 1984 DE
3536907 Feb 1989 DE
3404202 Dec 1992 DE
199311014 Oct 1993 DE
4414683 Oct 1995 DE
4338841 Aug 1999 DE
19849978 Feb 2001 DE
19849978 Feb 2001 DE
10242257 Apr 2003 DE
102004038074 Jun 2005 DE
10357636 Jul 2005 DE
102004041021 Aug 2005 DE
102005046813 Apr 2007 DE
198803389 Dec 1988 DK
265542 May 1988 EP
281085 Sep 1988 EP
307381 Jul 1990 EP
358628 May 1991 EP
437024 Jul 1991 EP
433697 Dec 1992 EP
479273 May 1993 EP
294101 Dec 1993 EP
554978 Mar 1994 EP
615719 Sep 1994 EP
861629 Sep 1998 EP
792726 Jun 1999 EP
930040 Oct 1999 EP
845237 Apr 2000 EP
1018315 Jul 2000 EP
1172719 Jan 2002 EP
1228734 Jun 2003 EP
1 331 537 Jul 2003 EP
1 331 537 Jul 2003 EP
1331537 Jul 2003 EP
1 380 245 Jan 2004 EP
1380246 Mar 2005 EP
1 557 730 Jul 2005 EP
1553472 Jul 2005 EP
1642522 Nov 2007 EP
2238196 Nov 2006 ES
2601443 Nov 1991 FR
2 828 589 Aug 2001 FR
702426 Jan 1954 GB
2128842 Apr 1986 GB
2213047 Aug 1989 GB
2225221 May 1990 GB
2 283 838 May 1995 GB
2284957 Jun 1995 GB
2267360 Dec 1995 GB
2300082 Sep 1999 GB
2404330 Jul 2005 GB
2417354 Feb 2006 GB
53021869 Feb 1978 JP
53110257 Sep 1978 JP
53110257 Sep 1978 JP
943901 Mar 1979 JP
57014726 Jan 1982 JP
57064217 Apr 1982 JP
59005315 Feb 1984 JP
59033511 Mar 1984 JP
59094005 May 1984 JP
59099308 Jul 1984 JP
59112311 Jul 1984 JP
59033511 Aug 1984 JP
59120124 Aug 1984 JP
59131668 Sep 1984 JP
59164973 Sep 1984 JP
59184917 Oct 1984 JP
2283343 Nov 1984 JP
59212924 Dec 1984 JP
59226909 Dec 1984 JP
60089213 May 1985 JP
60089213 Jun 1985 JP
60211510 Oct 1985 JP
60259895 Dec 1985 JP
61023221 Jan 1986 JP
61097712 May 1986 JP
61023221 Jun 1986 JP
62074018 Apr 1987 JP
62070709 May 1987 JP
6212051 Jul 1987 JP
62154008 Sep 1987 JP
62164431 Oct 1987 JP
62-263507 Nov 1987 JP
62263507 Nov 1987 JP
62263508 Nov 1987 JP
62189057 Dec 1987 JP
63079623 Apr 1988 JP
63-183032 Jul 1988 JP
63158032 Jul 1988 JP
63241610 Oct 1988 JP
1162454 Jun 1989 JP
2006312 Jan 1990 JP
2026312 Jun 1990 JP
2283343 Nov 1990 JP
3051023 Mar 1991 JP
3197758 Aug 1991 JP
3201903 Sep 1991 JP
4019586 Mar 1992 JP
4084921 Mar 1992 JP
5023269 Apr 1993 JP
5091604 Apr 1993 JP
5042076 Jun 1993 JP
5046246 Jun 1993 JP
5150827 Jun 1993 JP
5150829 Jun 1993 JP
5046239 Jul 1993 JP
5054620 Jul 1993 JP
5040519 Oct 1993 JP
5257527 Oct 1993 JP
5257533 Oct 1993 JP
5285861 Nov 1993 JP
6003251 Jan 1994 JP
6026312 Apr 1994 JP
6137828 May 1994 JP
6293095 Oct 1994 JP
6327598 Nov 1994 JP
6105781 Dec 1994 JP
7059702 Mar 1995 JP
7129239 May 1995 JP
7059702 Jun 1995 JP
7222705 Aug 1995 JP
7222705 Aug 1995 JP
7270518 Oct 1995 JP
7281742 Oct 1995 JP
7281752 Oct 1995 JP
7295636 Nov 1995 JP
7311041 Nov 1995 JP
7313417 Dec 1995 JP
7319542 Dec 1995 JP
8000393 Jan 1996 JP
8000393 Jan 1996 JP
8016241 Jan 1996 JP
8016776 Feb 1996 JP
8016776 Feb 1996 JP
08-083125 Mar 1996 JP
8063229 Mar 1996 JP
8083125 Mar 1996 JP
8083125 Mar 1996 JP
8089449 Apr 1996 JP
8089451 Apr 1996 JP
2520732 May 1996 JP
8123548 May 1996 JP
8152916 Jun 1996 JP
8152916 Jun 1996 JP
8256960 Oct 1996 JP
8263137 Oct 1996 JP
8286741 Nov 1996 JP
8286744 Nov 1996 JP
8322774 Dec 1996 JP
8322774 Dec 1996 JP
8335112 Dec 1996 JP
9043901 Feb 1997 JP
9044240 Feb 1997 JP
9047413 Feb 1997 JP
9066855 Mar 1997 JP
9145309 Jun 1997 JP
9160644 Jun 1997 JP
9160644 Jun 1997 JP
9179625 Jul 1997 JP
9179625 Jul 1997 JP
9179685 Jul 1997 JP
9185410 Jul 1997 JP
9192069 Jul 1997 JP
09-206258 Aug 1997 JP
9204223 Aug 1997 JP
9206258 Aug 1997 JP
9206258 Aug 1997 JP
09-233712 Sep 1997 JP
9233712 Sep 1997 JP
09251318 Sep 1997 JP
9251318 Sep 1997 JP
9265319 Oct 1997 JP
9269807 Oct 1997 JP
9269810 Oct 1997 JP
02555263 Nov 1997 JP
9319431 Dec 1997 JP
9319432 Dec 1997 JP
9319434 Dec 1997 JP
9325812 Dec 1997 JP
10055215 Feb 1998 JP
10117973 May 1998 JP
10117973 May 1998 JP
10118963 May 1998 JP
10177414 Jun 1998 JP
10214114 Aug 1998 JP
10214114 Aug 1998 JP
10228316 Aug 1998 JP
10240342 Sep 1998 JP
10260727 Sep 1998 JP
10295595 Nov 1998 JP
11015941 Jan 1999 JP
11065655 Mar 1999 JP
11085269 Mar 1999 JP
11102219 Apr 1999 JP
11102220 Apr 1999 JP
11162454 Jun 1999 JP
11174145 Jul 1999 JP
11175149 Jul 1999 JP
11178764 Jul 1999 JP
11178765 Jul 1999 JP
11212642 Aug 1999 JP
11212642 Aug 1999 JP
11213157 Aug 1999 JP
11508810 Aug 1999 JP
11-248806 Sep 1999 JP
11248806 Sep 1999 JP
11510935 Sep 1999 JP
11-282533 Oct 1999 JP
11282532 Oct 1999 JP
11282533 Oct 1999 JP
11295412 Oct 1999 JP
11346964 Dec 1999 JP
2000-047728 Feb 2000 JP
2000047728 Feb 2000 JP
2000056006 Feb 2000 JP
2000056831 Feb 2000 JP
2000066722 Mar 2000 JP
2000075925 Mar 2000 JP
10240343 May 2000 JP
2000275321 Oct 2000 JP
2000353014 Dec 2000 JP
2000353014 Dec 2000 JP
2001022443 Jan 2001 JP
2001067588 Mar 2001 JP
2001087182 Apr 2001 JP
2001087182 Apr 2001 JP
2001-125641 May 2001 JP
2001121455 May 2001 JP
2001125641 May 2001 JP
2001216482 Aug 2001 JP
2001258807 Sep 2001 JP
2001265437 Sep 2001 JP
2001275908 Oct 2001 JP
2001289939 Oct 2001 JP
2001306170 Nov 2001 JP
2001320781 Nov 2001 JP
2001525567 Dec 2001 JP
2002204768 Jul 2002 JP
2002204769 Jul 2002 JP
2002247510 Aug 2002 JP
2002532178 Oct 2002 JP
2002323925 Nov 2002 JP
2002333920 Nov 2002 JP
03356170 Dec 2002 JP
2002355206 Dec 2002 JP
2002360471 Dec 2002 JP
2002360479 Dec 2002 JP
2002360482 Dec 2002 JP
2002366227 Dec 2002 JP
2002369778 Dec 2002 JP
2002369778 Dec 2002 JP
2003005296 Jan 2003 JP
2003010076 Jan 2003 JP
2003010088 Jan 2003 JP
2003015740 Jan 2003 JP
2003028528 Jan 2003 JP
03375843 Feb 2003 JP
2003036116 Feb 2003 JP
2003047579 Feb 2003 JP
2003052596 Feb 2003 JP
2003505127 Feb 2003 JP
2003061882 Mar 2003 JP
2003084994 Mar 2003 JP
2003167628 Jun 2003 JP
2001-289939 Jul 2003 JP
2003-186539 Jul 2003 JP
2003180586 Jul 2003 JP
2003180587 Jul 2003 JP
2003186539 Jul 2003 JP
2003190064 Jul 2003 JP
2003190064 Jul 2003 JP
2003241836 Aug 2003 JP
2003262520 Sep 2003 JP
2003285288 Oct 2003 JP
2003304992 Oct 2003 JP
2003-330543 Nov 2003 JP
2003310489 Nov 2003 JP
2003310509 Nov 2003 JP
2003330543 Nov 2003 JP
2004123040 Apr 2004 JP
2004148021 May 2004 JP
2004160102 Jun 2004 JP
2004166968 Jun 2004 JP
2004174228 Jun 2004 JP
2004198330 Jul 2004 JP
2004219185 Aug 2004 JP
2005118354 May 2005 JP
2005135400 May 2005 JP
2005211360 Aug 2005 JP
2005224265 Aug 2005 JP
2005230032 Sep 2005 JP
2005245916 Sep 2005 JP
2005296511 Oct 2005 JP
2005346700 Dec 2005 JP
2005352707 Dec 2005 JP
2006043071 Feb 2006 JP
2006155274 Jun 2006 JP
2006164223 Jun 2006 JP
2006227673 Aug 2006 JP
2006247467 Sep 2006 JP
2006260161 Sep 2006 JP
2006293662 Oct 2006 JP
2006296697 Nov 2006 JP
2007034866 Feb 2007 JP
2007213180 Aug 2007 JP
04074285 Apr 2008 JP
2009015611 Jan 2009 JP
2010198552 Sep 2010 JP
WO9526512 Oct 1995 WO
WO9530887 Nov 1995 WO
WO9617258 Feb 1997 WO
WO9715224 May 1997 WO
WO9740734 Nov 1997 WO
WO9741451 Nov 1997 WO
WO9853456 Nov 1998 WO
WO9905580 Feb 1999 WO
WO9916078 Apr 1999 WO
WO9928800 Jun 1999 WO
WO9938056 Jul 1999 WO
WO9938237 Jul 1999 WO
WO9943250 Sep 1999 WO
WO9959042 Nov 1999 WO
WO0004430 Apr 2000 WO
WO0036962 Jun 2000 WO
WO0038026 Jun 2000 WO
WO0038028 Jun 2000 WO
WO0038029 Jun 2000 WO
WO0078410 Dec 2000 WO
WO0106905 Feb 2001 WO
WO0106904 Feb 2001 WO
WO0180703 Nov 2001 WO
WO0191623 Dec 2001 WO
WO0239864 May 2002 WO
WO0239868 May 2002 WO
WO02062194 Aug 2002 WO
WO02058527 Aug 2002 WO
WO02071175 Sep 2002 WO
WO02067744 Sep 2002 WO
WO02067745 Sep 2002 WO
WO02067752 Sep 2002 WO
WO02069774 Sep 2002 WO
WO02075350 Sep 2002 WO
WO02075356 Sep 2002 WO
WO02075469 Sep 2002 WO
WO02075470 Sep 2002 WO
WO02081074 Oct 2002 WO
WO03015220 Feb 2003 WO
WO03015220 Feb 2003 WO
WO03024292 Mar 2003 WO
WO02069775 May 2003 WO
WO03040546 May 2003 WO
WO03040845 May 2003 WO
WO03040846 May 2003 WO
WO03062850 Jul 2003 WO
WO03062852 Jul 2003 WO
WO02101477 Oct 2003 WO
WO03026474 Nov 2003 WO
WO2004004533 Jan 2004 WO
WO2005077244 Jan 2004 WO
WO2006068403 Jan 2004 WO
WO2004004534 Jan 2004 WO
WO2004005956 Jan 2004 WO
WO2004006034 Jan 2004 WO
WO2004025947 May 2004 WO
WO2004043215 May 2004 WO
WO2004058028 Jul 2004 WO
WO2004059409 Jul 2004 WO
WO2004058028 Jul 2004 WO
WO2005006935 Jan 2005 WO
WO2005036292 Apr 2005 WO
WO2005055795 Jun 2005 WO
WO2005055796 Jun 2005 WO
WO2005076545 Aug 2005 WO
WO2005077243 Aug 2005 WO
WO2005081074 Sep 2005 WO
WO2005081074 Sep 2005 WO
WO2005082223 Sep 2005 WO
WO2005083541 Sep 2005 WO
WO2005098475 Oct 2005 WO
WO2005098476 Oct 2005 WO
WO2006046400 May 2006 WO
WO2006061133 Jun 2006 WO
WO2006073248 Jul 2006 WO
WO2007036490 May 2007 WO
WO2007065033 Jun 2007 WO
WO2007137234 Nov 2007 WO
Non-Patent Literature Citations (242)
Entry
Wolf et al. “Robust Vision-based Localization for Mobile Robots Using an Image Retrieval System Based on Invariant Features”, Proceedings of the 2002 IEEE International Conference on Robotics & Automation, Washington, D.C. pp. 359-365, May 2002.
Wolf et al. “Robust Vision-Based Localization by Combining an Image-Retrieval System with Monte Carol Localization”, IEEE Transactions on Robotics, vol. 21, No. 2, pp. 208-216, Apr. 2005.
Wong “EIED Online>> Robot Business”, ED Online ID# 13114, 17 pages, Jul. 2006.
Yamamoto et al. “Optical Sensing for Robot Perception and Localization”, 2005 IEEE Workshop on Advanced Robotics and its Social Impacts, pp. 14-17, 2005.
Yata et al. “Wall Following Using Angle Information Measured by a Single Ultrasonic Transducer”, Proceedings of the 1998 IEEE, International Conference on Robotics & Automation, Leuven, Belgium, pp. 1590-1596, May 1998.
Yun, et al. “Image-Based Absolute Positioning System for Mobile Robot Navigation”, IAPR International Workshops SSPR, Hong Kong, pp. 261-269, Aug. 17-19, 2006.
Yun, et al. “Robust Positioning a Mobile Robot with Active Beacon Sensors”, Lecture Notes in Computer Science, 2006, vol. 4251, pp. 890-897, 2006.
Yuta, et al. “Implementation of an Active Optical Range sensor Using Laser Slit for In-Door Intelligent Mobile Robot”, IEE/RSJ International workshop on Intelligent Robots and systems (IROS 91) vol. 1, Osaka, Japan, pp. 415-420, Nov. 3-5, 1991.
Zha et al. “Mobile Robot Localization Using Incomplete Maps for Change Detection in a Dynamic Environment”, Advanced Intelligent Mechatronics '97. Final Program and Abstracts., IEEE/ASME International Conference, pp. 110, Jun. 16-20, 1997.
Zhang, et al. “A Novel Mobile Robot Localization Based on Vision”, SPIE vol. 6279, 6 pages, Jan. 29, 2007.
Roboking—not just a vacuum cleaner, a robot! Jan. 21, 2004, 5 pages.
Popco.net Make your digital life http://www.popco.net/zboard/view.php?id=tr—review&no=40 accessed Nov. 1, 2011.
Matsumura Camera Online Shop http://www.rakuten.co.jp/matsucame/587179/711512/ accessed Nov. 1, 2011.
Dyson's Robot Vacuum Cleaner—the DC06, May 2, 2004 http://www.gizmag.com/go/1282/ accessed Nov. 11, 2011.
Electrolux Trilobite, Time to enjoy life, 38 pages http://www.robocon.co.kr/trilobite/Presentation—Trilobite—Kor—030104.ppt accessed Dec. 22, 2011.
Facts on the Trilobite http://www.frc.ri.cmu.edu/˜hpm/talks/Extras/trilobite.desc.html 2 pages accessed Nov. 1, 2011.
Euroflex Jan. 1, 2006 http://www.euroflex.tv/novita—dett.php?id=15 1 page accessed Nov. 1, 2011.
Friendly Robotics, 18 pages http://www.robotsandrelax.com/PDFs/RV400Manual.pdf accessed Dec. 22, 2011.
It's eye, 2003 www.hitachi.co.jp/rd/pdf/topics/hitac2003—10.pdf 2 pages.
Hitachi, May 29, 2003 http://www.hitachi.co.jp/New/cnews/hl—030529—hl—030529.pdf 8 pages.
Robot Buying Guide, LG announces the first robotic vacuum cleaner for Korea, Apr. 21, 2003 http://robotbg.com/news/2003/04/22/lg—announces—the—first—robotic—vacu.
UBOT, cleaning robot capable of wiping with a wet duster, http://us.aving.net/news/view.php?articleId=23031, 4 pages accessed Nov. 1, 2011.
Taipei Times, Robotic vacuum by Matsuhita about ot undergo testing, Mar. 26, 2002 http://www.taipeitimes.com/News/worldbiz/archives/2002/03/26/0000129338 accessed.
Tech-on! http://techon.nikkeibp.co.jp/members/01db/200203/1006501/, 4 pages, accessed Nov. 1, 2011.
IT media http://www.itmedia.co.jp/news/0111/16/robofesta—m.html accessed Nov. 1, 2011.
Yujin Robotics, an intelligent cleaning robot ‘iclebo Q’ AVING USA http://us.aving.net/news/view.php?articleId=7257, 8 pages accessed Nov. 4, 2011.
Special Reports, Vacuum Cleaner Robot Operated in Conjunction with 3G Cellular Phone vol. 59, No. 9 (2004) 3 pages http://www.toshiba.co.jp/tech/review/2004/09/59—0.
Toshiba Corporation 2003, http://warp.ndl.go.jp/info:ndljp/pid/258151/www.soumu.go.jp/joho—tsusin/policyreports/chousa/netrobot/pdf/030214—1—33—a.pdf 16 pages.
http://www.karcher.de/versions/intg/assets/video/2—4—robo—en.swf. Accessed Sep. 25, 2009.
McLurkin “The Ants: A community of Microrobots”, Paper submitted for requirements of BSEE at MIT, May 12, 1995.
Grumet “Robots Clean House”, Popular Mechanics, Nov. 2003.
McLurkin Stupid Robot Tricks: A Behavior-based Distributed Algorithm Library for Programming Swarms of Robots, Paper submitted for requirements of BSEE at MIT, May 2004.
Kurs et al, Wireless Power transfer via Strongly Coupled Magnetic Resonances, Downloaded from www.sciencemag.org , Aug. 17, 2007.
OnRobo “Samsung Unveils Its Multifunction Robot Vacuum”, www.onrobo.com/enews/02101samsung—vacuum.shtml, 3 pages, Mar. 18, 2005.
Pages et al. “Optimizing Plane-to-Plane Positioning Tasks by Image-Based Visual Servoing and Structured Light”, IEEE Transactions on Robotics, vol. 22, No. 5, pp. 1000-1010, Oct. 2006.
Pages et al. “A camera-projector system for robot positioning by visual servoing”, Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW06), 8 pages, Jun. 17-22, 2006.
Pages, et al. “Robust decoupled visual servoing based on structured light”, 2005 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 2676-2681, 2005.
Park et al. “A Neural Network Based Real-Time Robot Tracking Controller Using Position Sensitive Detectors,” IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on Neutral Networks, Orlando, Florida pp. 2754-2758, Jun. 27-Jul. 2, 1994.
Park, et al. “Dynamic Visual Servo Control of Robot Manipulators using Neutral Networks”, The Korean Institute Telematics and Electronics, vol. 29-B, No. 10, pp. 771-779, Oct. 1992.
Paromtchik, et al. “Optical Guidance System for Multiple mobile Robots”, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation, vol. 3, pp. 2935-2940 (May 21-26, 2001).
Penna, et al. “Models for Map Building and Navigation”, IEEE Transactions on Systems. Man. and Cybernetics. vol. 23 No. 5, pp. 1276-1301, Sep./Oct. 1993.
Pirjanian “Reliable Reaction”, Proceedings of the 1996 IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems, pp. 158-165, 1996.
Pirjanian “Challenges for Standards for consumer Robotics”, IEEE Workshop on Advanced Robotics and its Social impacts, pp. 260-264, Jun. 12-15, 2005.
Pirjanian et al. “Distributed Control for a Modular, Reconfigurable Cliff Robot”, Proceedings of the 2002 IEEE International Conference on Robotics & Automation, Washington, D.C. pp. 4083-4088, May 2002.
Pirjanian et al. “Representation and Execution of Plan Sequences for Multi-Agent Systems”, Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, Hawaii, pp. 2117-2123, Oct. 29-Nov. 3, 2001.
Pirjanian et al. “Multi-Robot Target Acquisition using Multiple Objective Behavior Coordination”, Proceedings of the 2000 IEEE International Conference on Robotics & Automation, San Francisco, CA, pp. 2696-2702, Apr. 2000.
Pirjanian et al. “A decision-theoretic approach to fuzzy behavior coordination”, 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation, 1999. CIRA '99., Monterey, CA, pp. 101-106, Nov. 8-9, 1999.
Pirjanian et al. “Improving Task Reliability by Fusion of Redundant Homogeneous Modules Using Voting Schemes”, Proceedings of the 1997 IEEE International Conference on Robotics and Automation, Albuquerque, NM, pp. 425-430, Apr. 1997.
Prassler et al., “A Short History of Cleaning Robots”, Autonomous Robots 9, 211-226, 2000, 16 pages.
Remazeilles, et al. “Image based robot navigation in 3D environments”, Proc. of SPIE, vol. 6052, pp. 1-14, Dec. 6, 2005.
Rives, et al. “Visual servoing based on ellipse features”, SPIE vol. 2056 Intelligent Robots and Computer Vision pp. 356-367, 1993.
Robotics World Jan. 2001: “A Clean Sweep” (Jan. 2001).
Ronnback “On Methods for Assistive Mobile Robots”, http://www.openthesis.org/documents/methods-assistive-mobile-robots-595019.html, 218 pages, Jan. 1, 2006.
Roth-Tabak, et al. “Environment Model for mobile Robots Indoor Navigation”, SPIE vol. 1388 Mobile Robots pp. 453-463, 1990.
Sadath M Malik et al. “Virtual Prototyping for Conceptual Design of a Tracked Mobile Robot”. Electrical and Computer Engineering, Canadian Conference on, IEEE, PI. May 1, 2006, pp. 2349-2352.
Sahin, et al. “Development of a Visual Object Localization Module for Mobile Robots”, 1999 Third European Workshop on Advanced Mobile Robots, (Eurobot '99), pp. 65-72, 1999.
Salomon, et al. “Low-Cost Optical Indoor Localization system for Mobile Objects without Image Processing”, IEEE Conference on Emerging Technologies and Factory Automation, 2006. (ETFA '06), pp. 629-632, Sep. 20-22, 2006.
Sato “Range Imaging Based on Moving Pattern Light and Spatio-Temporal Matched Filter”, Proceedings International Conference on Image Processing, vol. 1., Lausanne, Switzerland, pp. 33-36, Sep. 16-19, 1996.
Schenker, et al. “Lightweight rovers for Mars science exploration and sample return”, Intelligent Robots and Computer Vision XVI, SPIE Proc. 3208, pp. 24-36, 1997.
Shimoga et al. “Touch and Force Reflection for Telepresence Surgery”, Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers. Proceedings of the 16th Annual International Conference of the IEEE, Baltimore, MD, pp. 1049-1050, 1994.
Sim, et al “Learning Visual Landmarks for Pose Estimation”, IEEE International Conference on Robotics and Automation, vol. 3, Detroit, MI, pp. 1972-1978, May 10-15, 1999.
Sobh et al. “Case Studies in Web-Controlled Devices and Remote Manipulation”, Automation Congress, 2002 Proceedings of the 5th Biannual World, pp. 435-440, Dec. 10, 2002.
Stella, et al. “Self-Location for Indoor Navigation of Autonomous Vehicles”, Part of the SPIE conference on Enhanced and Synthetic Vision SPIE vol. 3364 pp. 298-302, 1998.
Summet “Tracking Locations of Moving Hand-held Displays Using Projected Light”, Pervasive 2005, LNCS 3468 pp. 37-46 (2005).
Svedman et al. “Structure from Stereo Vision using Unsynchronized Cameras for Simultaneous Localization and Mapping”, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2993-2998, 2005.
Takio et al. “Real-Time Position and Pose Tracking Method of Moving Object Using Visual Servo System”, 47th IEEE International Symposium on Circuits and Systems, pp. 167-170, 2004.
Teller “Pervasive pose awareness for people, Objects and Robots”, http://www.ai.mit.edu/lab/dangerous-ideas/Spring2003/teller-pose.pdf, 6 pages, Apr. 30, 2003.
Terada et al. “An Acquisition of the Relation between Vision and Action using Self-Organizing Map and Reinforcement Learning”, 1998 Second International Conference on Knowledge-Based Intelligent Electronic Systems, Adelaide, Australiam pp. 429-434, Apr. 21-23, 1998.
The Sharper Image “Robotic Vacuum Cleaner—Blue” www.Sharperimage.com, 2 pages, Mar. 18, 2005.
The Sharper Image “E Vac Robotic Vacuum”, www.sharperiamge.com/us/en/templates/products/pipmorework1printable.jhtml, 2 pages, Mar. 18, 2005.
TheRobotStore.com “Friendly Robotics Robotic Vacuum RV400—The Robot Store”, www.therobotstore.com/s.nl/sc.9/category.-109/it.A/id.43/.f, 1 page, Apr. 20, 2005.
TotalVac.com RC3000 RoboCleaner website Mar. 18, 2005.
Trebi-Ollennu et al. “Mars Rover Pair Cooperatively Transporting a Long Payload”, Proceedings of the 2002 IEEE International Conference on Robotics & Automation, Washington, D.C. pp. 3136-3141, May 2002.
Tribelhorn et al., “Evaluating the Roomba: A low-cost, ubiquitous platform for robotics research and education,” 2007, IEEE, p. 1393-1399.
Tse et al. “Design of a Navigation System for a Household Mobile Robot Using Neural Networks”, Department of Manufacturing Engg. & Engg. Management, City University of Hong Kong, pp. 2151-2156, 1998.
UAMA (Asia) Industrial Co., Ltd. “RobotFamily”, 2005.
Watanabe et al. “Position Estimation of Mobile Robots With Internal and External Sensors Using Uncertainty Evolution Technique”, 1990 IEEE International Conference on Robotics and Automation, Cincinnati, OH, pp. 2011-2016, May 13-18, 1990.
Watts “Robot, boldly goes where no man can”, The Times—pp. 20, Jan. 1985.
Wijk et al. “Triangulation-Based Fusion of Sonar Data with Application in Robot Pose Tracking ”, IEEE Transactions on Robotics and Automation, vol. 16, No. 6, pp. 740-752, Dec. 2000.
Jarosiewicz et al. “Final Report—Lucid”, University of Florida, Departmetn of Electrical and Computer Engineering, EEL 5666—Intelligent Machine Design Laboratory, 50 pages, Aug. 4, 1999.
Jensfelt, et al. “Active Global Localization for a mobile robot using multiple hypothesis tracking”, IEEE Transactions on Robots and Automation vol. 17, No. 5, pp. 748-760, Oct. 2001.
Jeong, et al. “An intelligent map-building system for indoor mobile robot using low cost photo sensors”, SPIE vol. 6042 6 pages, 2005.
Kahney, “Robot Vacs are in the House,” www.wired.com/news/technology/o,1282,59237,00.html, 6 pages, Jun. 18, 2003.
Karcher “Product Manual Download Karch”, www.karcher.com, 17 pages, 2004.
Karcher “Karcher RoboCleaner RC 3000”, www.robocleaner.de/english/screen3.html, 4 pages, Dec. 12, 2003.
Karcher USA “RC 3000 Robotics cleaner”, www.karcher-usa.com, 3 pages, Mar. 18, 2005.
Karlsson et al., The vSLAM Algorithm for Robust Localization and Mapping, Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 24-29, Apr. 2005.
Karlsson, et al Core Technologies for service Robotics, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2004), vol. 3, pp. 2979-2984, Sep. 28-Oct. 2, 2004.
King “Heplmate-TM—Autonomous mobile Robots Navigation Systems”, SPIE vol. 1388 Mobile Robots pp. 190-198, 1990.
Kleinberg, The Localization Problem for Mobile Robots, Laboratory for Computer Science, Massachusetts Institute of Technology, 1994 IEEE, pp. 521-531, 1994.
Knight, et al., “Localization and Identification of Visual Landmarks”, Journal of Computing Sciences in Colleges, vol. 16 Issue 4, 2001 pp. 312-313, May 2001.
Kolodko et al. “Experimental System for Real-Time Motion Estimation”, Proceedings of the 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), pp. 981-986, 2003.
Komoriya et al., Planning of Landmark Measurement for the Navigation of a Mobile Robot, Proceedings of the 1992 IEEE/RSJ International Cofnerence on Intelligent Robots and Systems, Raleigh, NC pp. 1476-1481, Jul. 7-10, 1992.
Krotov, et al. “Digital Sextant”, Downloaded from the internet at: http://www.cs.cmu.edu/˜epk/ , 1 page, 1995.
Krupa et al. “Autonomous 3-D Positioning of Surgical Instruments in Robotized Laparoscopic Surgery Using Visual Servoing”, IEEE Transactions on Robotics and Automation, vol. 19, No. 5, pp. 842-853, Oct. 5, 2003.
Kuhl, et al. “Self Localization in Environments using Visual Angles”, VRCAI '04 Proceedings of the 2004 ACM SIGGRAPH international conference on Virtual Reality continuum and its applications in industry, pp. 472-475, 2004.
Kurth, “Range-Only Robot Localization and SLAM with Radio”, http://www.ri.cmu.edu/pub—files/pub4/kurth—derek—2004—1/kurth—derek—2004—1.pdf. 60 pages, May 2004.
Lambrinos, et al. “A mobile robot employing insect strategies for navigation”, http://www8.cs.umu.se/kurser/TDBD17/VT04/dl/Assignment%20Papers/lambrinos-RAS-2000.pdf, 38 pages, Feb. 19, 1999.
Lang et al. “Visual Measurement of Orientation Using Ceiling Features”, 1994 IEEE, pp. 552-555, 1994.
Lapin, “Adaptive position estimation for an automated guided vehicle”, SPIE vol. 1831 Mobile Robots VII, pp. 82-94, 1992.
LaValle et al. “Robot Motion Planning in a Changing, Partially Predictable Environment”, 1994 IEEE International Symposium on Intelligent Control, Columbus, OH, pp. 261-266, Aug. 16-18, 1994.
Lee, et al. “Localization of a Mobile Robot Using the Image of a Moving Object”, IEEE Transaction on Industrial Electronics, vol. 50, No. 3 pp. 612-619, Jun. 2003.
Lee, et al. “Development of Indoor Navigation system for Humanoid Robot Using Multi-sensors Integration”, ION NTM, San Diego, CA pp. 798-805, Jan. 22-24, 2007.
Leonard, et al. “Mobile Robot Localization by tracking Geometric Beacons”, IEEE Transaction on Robotics and Automation, vol. 7, No. 3 pp. 376-382, Jun. 1991.
Li et al. “Making a Local Map of Indoor Environments by Swiveling a Camera and a Sonar”, Proceedings of the 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 954-959, 1999.
Lin, et al.. “Mobile Robot Navigation Using Artificial Landmarks”, Journal of robotics System 14(2). pp. 93-106, 1997.
Linde “Dissertation, “On Aspects of Indoor Localization”” https://eldorado.tu-dortmund.de/handle/2003/22854, University of Dortmund, 138 pages, Aug. 28, 2006.
Lumelsky, et al. “An Algorithm for Maze Searching with Azimuth Input”, 1994 IEEE International Conference on Robotics and Automation, San Diego, CA vol. 1, pp. 111-116, 1994.
Luo et al., “Real-time Area-Covering Operations with Obstacle Avoidance for Cleaning Robots,” 2002, IEeE, p. 2359-2364.
Ma “Thesis: Documentation on Northstar”, California Institute of Technology, 14 pages, May 17, 2006.
Madsen, et al. “Optimal landmark selection for triangulation of robot position”, Journal of Robotics and Autonomous Systems vol. 13 pp. 277-292, 1998.
Matsutek Enterprises Co. Ltd “Automatic Rechargeable Vacuum Cleaner”, http://matsutek.manufacturer.globalsources.com/si/6008801427181/pdtl/Home-vacuum/10 . . . , Apr. 23, 2007.
McGillem, et al. “Infra-red Lacation System for Navigation and Autonomous Vehicles”, 1988 IEEE International Conference on Robotics and Automation, vol. 2, pp. 1236-1238, Apr. 24-29, 1988.
McGillem,et al. “A Beacon Navigation Method for Autonomous Vehicles”, IEEE Transactions on Vehicular Technology, vol. 38, No. 3, pp. 132-139, Aug. 1989.
Michelson “Autonomous Navigation”, 2000 Yearbook of Science & Technology, McGraw-Hill, New York, ISBN 0-07-052771-7, pp. 28-30, 1999.
Miro, et al. “Towards Vision Based Navigation in Large Indoor Environments”, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, pp. 2096-2102, Oct. 9-15, 2006.
MobileMag “Samsung Unveils High-tech Robot Vacuum Cleaner”, http://www.mobilemag.com/content/100/102/C2261/, 4 pages, Mar. 18, 2005.
Monteiro, et al. “Visual Servoing for Fast Mobile Robot: Adaptive Estimation of Kinematic Parameters”, Proceedings of the IECON '93., International Conference on Industrial Electronics, Maui, HI, pp. 1588-1593, Nov. 15-19, 1993.
Moore, et al. A simple Map-bases Localization strategy using range measurements, SPIE vol. 5804 pp. 612-620, 2005.
Munich et al. “SIFT-ing Through Features with ViPR”, IEEE Robotics & Automation Magazine, pp. 72-77, Sep. 2006.
Munich et al. “ERSP: A Software Platform and Architecture for the Service Robotics Industry”, Intelligent Robots and Systems, 2005. (IROS 2005), pp. 460-467, Aug. 2-6, 2005.
Nam, et al. “Real-Time Dynamic Visual Tracking Using PSD Sensors and extended Trapezoidal Motion Planning”, Applied Intelligence 10, pp. 53-70, 1999.
Nitu et al. “Optomechatronic System for Position Detection of a Mobile Mini-Robot”, IEEE Ttransactions on Industrial Electronics, vol. 52, No. 4, pp. 969-973, Aug. 2005.
On Robo “Robot Reviews Samsung Robot Vacuum (VC-RP30W)”, www.onrobo.com/reviews/AT—Home/vacuum—cleaners/on00vcrb30rosam/index.htm.. 2 pages, 2005.
InMach “Intelligent Machines”, www.inmach.de/inside.html, 1 page , Nov. 19, 2008.
Innovation First “2004 EDU Robot Controller Reference Guide”, http://www.ifirobotics.com, 13 pgs., Mar. 1, 2004.
Authorised Officer Aaron Piggush, Office Action received for U.S. Appl. No. 11/648,241, dated Mar. 18, 2011, 11 pages.
Authorised Officer Aaron Piggush, Office Action received for U.S. Appl. No. 11/648,230, dated Mar. 2, 2011, 11 pages.
Authorised Officer Amod Pradhan, Office Action received for Australian Patent Application No. 2010212297, mailed on Feb. 16, 2011, 3 pages.
Authorised Officer Amod Pradhan, Office Action received for Australian Patent Application No. 2004316156, mailed on Feb. 13, 2009, 2 pages.
Authorised Officer Joaquin Vano Gea, Extended Search Report received for European Patent Application No. 10181174.3, mailed on Feb. 10, 2011, 6 pages.
Authorised Officer Joaquin Vano Gea, Extended Search Report received for corresponding European Patent Application No. 1 0181187.5, mailed on Feb. 10, 2011, 8 pages.
Authorised Officer Joaquin Vano Gea, Office Action received for European Patent Application No. 1 0160949.3, mailed on Mar. 17, 2011, 5 pages.
Authorised Officer Joaquin Vano Gea, Office Action received for European Patent Application No. 04704061.3, mailed on Mar. 6, 2007, 4 pages.
Authorised Officer Joaquin Vano Gea, Office Action received for European Patent Application No. 04704061.3, mailed on Nov. 30, 2007,4 pages.
Authorised Officer Muhammad Haramain Osman, Office Action received for Singapore Patent Application No. 200505559-5, mailed on Oct. 30, 2007,4 pages.
Cameron Morland, Autonomous Lawn Mower Control, Jul. 24, 2002.
Examination report dated Jan. 7, 2008 for U.S. Appl. No. 11/648,241.
Examination report dated Jan. 27, 2009 for U.S. Appl. No. 11/648,241.
Examination report dated Jan. 30, 2006 for U.S. Appl. No. 10/762,219.
Examination report dated Feb. 25, 2008 for U.S. Appl. No. 11/648,230.
Examination report dated Apr. 2, 2010 for U.S. Appl. No. 11/648,241.
Examination report dated Apr. 6, 2009 for U.S. Appl. No. 11/648,230.
Examination report dated May 14, 2007 for U.S. Appl. No. 10/762,219.
Examination report dated Jul. 29, 2008 for U.S. Appl. No. 11/648,241.
Examination report dated Oct. 17, 2008 for U.S. Appl. No. 11/648,230.
Examination report dated Nov. 12, 2009 for U.S. Appl. No. 11/648,230.
Examination report dated Aug. 12, 2010 for corresponding application (KR) 10-2006-7014807.
Examination report dated Aug. 12, 2010 for corresponding application (KR) 10-2009-7025882.
Examination report dated Jun. 11, 2010 for U.S. Appl. No. 11/648,230.
Examination report dated May 27, 2010 for corresponding application (EP) 10160949.3.
Examination report dated Sep. 10, 2008 for corresponding application (EP) 08151962.1.
Examination report dated Feb. 16, 2011 from corresponding Australian Patent Application No. 2010212297.
Extended Search Report dated Feb. 10, 2011 from corresponding EP Application No. 10181187.
Extended Search Report received for European Patent Application No. 10181174.3, mailed on Feb. 10, 2011, 6 pages.
JP 2006-551013; Office Action dated Apr. 27, 2009 for Japanese counterpart application (7 pages).
JP 2007-10829; Office Action dated May 11, 2009 for Japanese counterpart application (6 pages).
JP2006-551013; Office Action dated Apr. 27, 2009 for Japanese counterpart (7 pages).
Office Action received for Australian Patent Application No. 2004316156, mailed on Feb. 13, 2009, 2 pages.
Office Action received for European Patent Application No. 04704061.3, mailed on Mar. 6, 2007, 4 pages.
Office Action received for European Patent Application No. 04704061.3, mailed on Nov. 30, 2007, 4 pages.
Office Action received for European Patent Application No. 10160949.3, mailed on Mar. 17, 2011, 5 pages.
Office Action received for Korean Patent Application No. 10-2006-7014807, mailed on May 10, 2011.
Office Action received for Korean Patent Application No. 10-2009-7025882, mailed on May 10, 2011.
Office Action received for Korean Patent Application No. 1 0-201 0-7025523, mailed on Feb. 15, 20011, 11 pages including English translation.
Office Action received for Korean Patent Application No. 10-2010-7025523, mailed on Feb. 15, 2011, 11 pages including English translation.
Office Action received for Singapore Patent Application No. 200505559-5, mailed on Oct. 30, 2007,4 pages.
Office Action received for U.S. Appl. No. 11/834,575, mailed on May 29, 2009.
Office Action received for U.S. Appl. No. 11/834,575, mailed on May 5, 2008.
Office Action received for U.S. Appl. No. 11/834,575, mailed on Nov. 28, 2008.
Office Action received for U.S. Appl. No. 11/648,241, dated Mar. 18, 2011, 11 pages.
Prassler et al. “A Short History of Cleaning Robots” Autonomous Robots 9, 211-226, 2000.
Written Opinion for corresponding application PCT/US2004/001504.
Borges et al. “Optimal Mobile Robot Pose Estimation Using Geometrical Maps”, IEEE Transactions on Robotics and Automation, vol. 18, No. 1, pp. 87-94, Feb. 2002.
Braunstingl et al. “Fuzzy Logic Wall Following of a Mobile Robot Based on the Concept of General Perception” ICAR '95, 7th International Conference on Advanced Robotics, Sant Feliu De Guixols, Spain, pp. 367-376, Sep. 1995.
Bulusu, et al. “Self Configuring Localization systems: Design and Experimental Evaluation”, ACM Transactions on Embedded Computing Systems vol. 3 No. 1 pp. 24-60, 2003.
Caccia, et al. “Bottom-Following for Remotely Operated Vehicles”, 5th IFAC conference, Alaborg, Denmark, pp. 245-250 Aug. 1, 2000.
Chae, et al. “StarLITE: A new artificial landmark for the navigation of mobile robots”, http://www.irc.atr.jp/jk-nrs2005/pdf/Starlite.pdf, 4 pages, 2005.
Chamberlin et al. “Team 1: Robot Locator Beacon System” NASA Goddard SFC, Design Proposal, 15 pages, Feb. 17, 2006.
Champy “Physical management of IT assets in Data Centers using RFID technologies”, RFID 2005 University, Oct. 12-14, 2005.
Chiri “Joystick Control for Tiny OS Robot”, http://www.eecs.berkeley.edu/Programs/ugrad/superb/papers2002/chiri.pdf. 12 pages, Aug. 8, 2002.
Christensen et al. “Theoretical Methods for Planning and Control in Mobile Robotics” 1997 First International Conference on Knowledge-Based Intelligent Electronic Systems, Adelaide, Australia, pp. 81-86, May 21-27, 1997.
Clerentin, et al. “A localization method based on two omnidirectional perception systems cooperation” Proc of IEEE International Conference on Robotics & Automation, San Francisco, CA vol. 2, pp. 1219-1224, Apr. 2000.
Corke “High Performance Visual serving for robots end-point control”. SPIE vol. 2056 Intelligent robots and computer vision 1993.
Cozman et al. “Robot Localization using a Computer Vision Sextant”, IEEE International Midwest Conference on Robotics and Automation, pp. 106-111, 1995.
D'Orazio, et al. “Model based Vision System for mobile robot position estimation”, SPIE vol. 2058 Mobile Robots VIII, pp. 38-49, 1992.
De Bakker, et al. “Smart PSD-array for sheet of light range imaging”, Proc. of SPIE vol. 3965, pp. 1-12, May 15, 2000.
Desaulniers, et al. “An Efficient Algorithm to find a shortest path for a car-like Robot”, IEEE Transactions on robotics and Automation vol. 11 No. 6, pp. 819-828, Dec. 1995.
Dorfmüller-Ulhaas “Optical Tracking From User Motion to 3D Interaction”, http://www.cg.tuwien.ac.at/research/publications/2002/Dorfmueller-Ulhaas-thesis, 182 pages, 2002.
Dorsch, et al. “Laser Triangulation: Fundamental uncertainty in distance measurement”, Applied Optics, vol. 33 No. 7, pp. 1306-1314, Mar. 1, 1994.
Dudek, et al. “Localizing a Robot with Minimum Travel” Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms, vol. 27 No. 2 pp. 583-604, Apr. 1998.
Dulimarta, et al. “Mobile Robot Localization in Indoor Environment”, Pattern Recognition, vol. 30, No. 1, pp. 99-111, 1997.
EBay “Roomba Timer -> Timed Cleaning—Floorvac Robotic Vacuum”, Cgi.ebay.com/ws/eBay|SAP|.dll?viewitem&category=43526&item=4375198387&rd=1, 5 pages, Apr. 20, 2005.
Electrolux “Welcome to the Electrolux trilobite” www.electroluxusa.com/node57.asp?currentURL=node142.asp%3F, 2 pages, Mar. 18, 2005.
Eren, et al. “Accuracy in position estimation of mobile robots based on coded infrared signal transmission”, Proceedings: Integrating Intelligent Instrumentation and Control, Instrumentation and Measurement Technology Conference, 1995. IMTC/95. pp. 548-551, 1995.
Eren, et al. “Operation of Mobile Robots in a Structured Infrared Environment”, Proceedings. ‘Sensing, Processing, Networking’, IEEE Instrumentation and Measurement Technology Conference, 1997 (IMTC/97), Ottawa, Canada vol. 1, pp. 20-25, May 19-21, 1997.
Becker, et al. “Reliable Navigation Using Landmarks” IEEE International Conference on Robotics and Automation, 0-7803-1965-6, pp. 401-406, 1995.
Benayad-Cherif, et al., “Mobile Robot Navigation Sensors” SPIE vol. 1831 Mobile Robots, VII, pp. 378-387, 1992.
Facchinetti, Claudio et al. “Using and Learning Vision-Based Self-Positioning for Autonomous Robot Navigation”, ICARCV '94, vol. 3 pp. 1694-1698, 1994.
Betke, et al., “Mobile Robot localization using Landmarks” Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems '94 “Advanced Robotic Systems and the Real World” (IROS '94), vol.
Facchinetti, Claudio et al. “Self-Positioning Robot Navigation Using Ceiling Images Sequences”, ACCV '95, 5 pages, Dec. 5-8, 1995.
Fairfield, Nathaniel et al. “Mobile Robot Localization with Sparse Landmarks”, SPIE vol. 4573 pp. 148-155, 2002.
Favre-Bulle, Bernard “Efficient tracking of 3D—Robot Position by Dynamic Triangulation”, IEEE Instrumentation and Measurement Technology Conference IMTC 98 Session on Instrumentation and Measurement in Robotics, vol. 1, pp. 446-449, May 18-21, 1998.
Fayman “Exploiting Process Integration and Composition in the context of Active Vision”, IEEE Transactions on Systems, Man, and Cybernetics—Part C: Application and reviews, vol. 29 No. 1, pp. 73-86, Feb. 1999.
Florbot GE Plastics Image (1989-1990).
Franz, et al. “Biomimetric robot navigation”, Robotics and Autonomous Systems vol. 30 pp. 133-153, 2000.
Friendly Robotics “Friendly Robotics—Friendly Vac, Robotic Vacuum Cleaner”, www.friendlyrobotics.com/vac.htm. 5 pages Apr. 20, 2005.
Fuentes, et al. “Mobile Robotics 1994”, University of Rochester. Computer Science Department, TR 588, 44 pages, Dec. 7, 1994.
Bison, P et al., “Using a structured beacon for cooperative position estimation” Robotics and Autonomous Systems vol. 29, No. 1, pp. 33-40, Oct. 1999.
Fukuda, et al. “Navigation System based on Ceiling Landmark Recognition for Autonomous mobile robot”, 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems 95. ‘Human Robot Interaction and Cooperative Robots’, Pittsburgh, PA, pp. 1466/1471, Aug. 5-9, 1995.
Gionis “A hand-held optical surface scanner for environmental Modeling and Virtual Reality”, Virtual Reality World, 16 pages 1996.
Goncalves et al. “A Visual Front-End for Simultaneous Localization and Mapping”, Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 44-49, Apr. 2005.
Gregg et al. “Autonomous Lawn Care Applications”, 2006 Florida Conference on Recent Advances in Robotics, FCRAR 2006, pp. 1-5, May 25-26, 2006.
Hamamatsu “SI PIN Diode S5980, S5981 S5870—Multi-element photodiodes for surface mounting”, Hamatsu Photonics, 2 pages Apr. 2004.
Hammacher Schlemmer “Electrolux Trilobite Robotic Vacuum” www.hammacher.com/publish/71579.asp?promo=xsells, 3 pages, Mar. 18, 2005.
Haralick et al. “Pose Estimation from Corresponding Point Data”, IEEE Transactions on systems, Man, and Cybernetics, vol. 19, No. 6, pp. 1426-1446, Nov. 1989.
Hausler “About the Scaling Behaviour of Optical Range Sensors”, Fringe '97, Proceedings of the 3rd International Workshop on Automatic Processing of Fringe Patterns, Bremen, Germany, pp. 147-155, Sep. 15-17, 1997.
Blaasvaer, et al. “AMOR—An Autonomous Mobile Robot Navigation System”, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 2266-2271, 1994.
Hoag, et al. “Navigation and Guidance in interstellar space”, ACTA Astronautica vol. 2, pp. 513-533 , Feb. 14, 1975.
Huntsberger et al. “CAMPOUT: A Control Architecture for Tightly Coupled Coordination of Multirobot Systems for Planetary Surface Exploration”, IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans, vol. 33, No. 5, pp. 550-559, Sep. 2003.
Iirobotics.com “Samsung Unveils Its Multifunction Robot Vacuum”, www.iirobotics.com/webpages/hotstuff.php?ubre=111, 3 pages, Mar. 18, 2005.
Andersen et al., “Landmark based navigation strategies”, SPIE Conference on Mobile Robots XIII, SPIE vol. 3525, pp. 170-181, Jan. 8, 1999.
Ascii, Mar. 25, 2002, http://ascii.jp/elem/000/000/330/330024/ accessed Nov. 1, 2011.
Electrolux Trilobite, Jan. 12, 2001, http://www.electrolux-ui.com:8080/2002%5C822%5C833102EN.pdf, accessed Jul. 2, 2012, 10 pages.
Li et al. “Robust Statistical Methods for Securing Wireless Localization in Sensor Networks,” Information Procesing in Sensor Networks, 2005, Fourth International Symposium on, pp. 91-98, Apr. 2005.
Maschinemarkt Würzburg 105, Nr. 27, pp. 3, 30, Jul. 5, 1999.
Martishevcky, “The Accuracy of point light target coordinate determination by dissectoral tracking system”, SPIE vol. 2591, pp. 25-30, Oct. 23, 2005.
Paromtchik “Toward Optical Guidance of Mobile Robots,” Proceedings of the Fourth World Multiconference on Systemics, Cybermetics and Informatics, Orlando, FL, USA, Jul. 23, 2000, vol. IX, pp. 44-49, available at http://emotion.inrialpes.fr/˜paromt/infos/papers/paromtchik:asama:sci:2000.ps.gz, accessed Jul. 3, 2012.
Roboking—not just a vacuum cleaner, a robot!, Jan. 21, 2004, infocom.uz/2004/01/21/robokingne-prosto-pyilesos-a-robot/, accessed Oct. 10, 2011, 7 pages.
Sebastian Thrun, “Learning Occupancy Grid Maps With Forward Sensor Models,” Autonomous Robots 15, 111-127, Sep. 1, 2003.
SVET Computers—New Technologies—Robot Vacuum Cleaner, Oct. 1999, available at http://www.sk.rs/1999/10/sknt01.html, accessed Nov. 1, 2011.
Certified copy of U.S. Appl. No. 60/605,066 as provided to WIPO in PCT/US2005/030422, corresponding to U.S. Appl. No. 11/574,290, U.S. publication 2008/0184518, filed Aug. 27, 2004.
Certified copy of U.S. Appl. No. 60/605,181 as provided to WIPO in PCT/US2005/030422, corresponding to U.S. Appl. No. 11/574,290, U.S. publication 2008/0184518, filed Aug. 27, 2004.
Derek Kurth, “Range-Only Robot Localization and SLAM with Radio”, http://www.ri.cmu.edu/pub—files/pub4/kurth—derek—2004—1/kurth—derek—2004—1.pdf. 60 pages, May 2004, accessed Jul. 27, 2012.
Florbot GE Plastics, 1989-1990, 2 pages, available at http://www.fuseid.com/, accessed Sep. 27, 2012.
Gregg et al., “Autonomous Lawn Care Applications,” 2006 Florida Conference on Recent Advances in Robotics, Miami, Florida, May 25-26, 2006, Florida International University, 5 pages.
Hitachi ‘Feature’, http://kadenfan.hitachi.co.jp/robot/feature/feature.html, 1 page, Nov. 19, 2008.
Hitachi, http://www.hitachi.co.jp/New/cnews/hi—030529—hi—030529.pdf , 8 pages, May 29, 2003.
Home Robot—UBOT; Microbotusa.com, retrieved from the WWW at www.microrobotusa.com, accessed Dec. 2, 2008.
King and Weiman, “Helpmate™ Autonomous Mobile Robots Navigation Systems,” SPIE vol. 1388 Mobile Robots, pp. 190-198 (1990).
Miwako Doi “Using the symbiosis of human and robots from approaching Research and Development Center,” Toshiba Corporation, 16 pages, available at http://warp.ndl.go.jp/info:ndljp/pid/258151/www.soumu.go.jp/joho—tsusin/policyreports/chousa/netrobot/pdf/030214—1—33—a.pdf, Feb. 26, 2003.
Written Opinion of the International Searching Authority, PCT/US2004/001504, Aug. 20, 2012, 9 pages.
Related Publications (1)
Number Date Country
20120049798 A1 Mar 2012 US
Divisions (1)
Number Date Country
Parent 10762219 Jan 2004 US
Child 11648230 US
Continuations (1)
Number Date Country
Parent 11648230 Dec 2006 US
Child 13291633 US