This invention relates to autonomous robot localization.
Autonomous robots that perform household functions such as floor cleaning and lawn cutting are now readily available consumer products. Commercially successful robots are not unnecessarily complex, and generally operate randomly within a confined area. In the case of floor cleaning, such robots are generally confined within (i) touched walls and other obstacles within the rooms of a dwelling, (ii) IR-detected staircases (cliffs) down; and/or (iii) user placed detectable barriers such as directed IR beams, physical barriers or magnetic tape. Other robots map the dwelling using a complex system of sensors and/or active or passive beacons (e.g., sonar, RFID or bar code detection, or various kinds of machine vision).
Some consumer robotic lawn mowers use a similar “invisible” barrier—a continuous guide conductor boundary (e.g., a boundary wire) for confining random motion robotic mowers. The boundary wire is intended to confine the robot within the lawn or other appropriate area, so as to avoid damaging non-grassy areas of the yard or intruding onto a neighboring property. Some consumer robotic lawn mowers use localization systems that make use of triangulation to determine the robot position within the boundary. For example, multiple beacons are positioned around the property to be mowed. Signals sent between the beacons and the lawnmower positioned in the property allow the lawnmower to estimate the angles and the distance by calculating time-of-flight to each of the beacons, and using trigonometry to calculate the robot's current position. In another example, the system can triangulate the distance to an object using a fixed-angle laser pointer and a CMOS imager, with a baseline between the two. In such examples, the pixel location of the received signal at the imager is indicative of the distance to the object.
There are several challenges in determining the position of an outdoor robot within a barrier. The resolution of current commercially available GPS applications is inadequate for this application (e.g., resolution is insufficient to prevent the lawnmower from not mowing a flower bed or other “no-mow” zone), particularly in light of tree cover commonly found in lawns. The variation in terrain also makes it difficult for the robot to “see” boundary markers; tilt or slant in the lawn can cause a moving mower having a sweeping beacon detector to not engage, or miss, a beacon. The additional costs and power requirements to improve these factors are important for consumers.
In some implementations, a location estimation system for use with an autonomous lawn mowing robot, the system comprises a plurality of synthetic surfaces positioned with respect to a mowable space in an environment, a radiation source coupled to the lawn mowing robot, a detector coupled to the lawn mowing robot and configured to detect radiation reflected by objects in the environment, and a controller configured to controllably direct radiation from the radiation source to scan the environment, and to vary at least one of an output power of the directed radiation and a scan rate of the directed radiation, as a function of detected radiation reflected from one or more of the synthetic surfaces. In further implementations, the controller is configured to vary a spin rate of the radiation source. The location estimation system comprises a modulator coupled to the radiation source and configured to modulate radiation emitted from the radiation source. The controller is configured to direct the modulator to vary the output power of the radiation source in response to detection of reflected radiation. The controller is configured to direct the modulator to vary a beam focus of the radiation source in response to detection of reflected radiation.
In further implementations, the location estimation system comprises a mechanical scanner that directs radiation from the radiation source to scan the environment. The system comprises a rotational scanner that directs radiation from the radiation source to scan the environment. The controller is further configured to compare data indicative of detected reflected radiation to stored data, and to identify the detected radiation as radiation reflected from a particular object associated with the stored data. The particular object is one of the synthetic surfaces. The particular object is a stationary non-retroreflective object within the environment. The controller is further configured to direct the radiation source to make a first scan of the environment at a first scan rate. The controller is configured to direct the radiation source to make a second scan of the environment at a second scan rate different from the first scan rate. The modulator is configured to direct the radiation source to make a second scan of the environment, a limited portion of the second scan performed at a second scan rate different from the first scan rate. The system further comprises a second detector of a different wavelength responsiveness than a first detector. The radiation source is a laser. The radiation is emitted across a distributed plane. The plane extends at 45 degrees to a surface supporting the autonomous lawn mowing robot. The controller is configured to modulate the output power of the radiation source. The controller is configured to perform a scan of the environment and to store resulting data indicative of reflected radiation detected by the detector during the scan. The synthetic surfaces are positioned at locations bordering the environment. The radiation source scans during a motion of the autonomous lawn mowing robot. The controller is coupled to the autonomous lawn mowing robot.
In other aspects of this disclosure, a method of estimating a location of a self-propelled lawn mowing robot in an environment, the method comprises positioning a plurality of synthetic surfaces at locations with respect to a mowable space in an environment, and placing a lawn mowing robot in the environment, the robot comprising: a radiation source coupled to the lawn mowing robot, a detector coupled to the lawn mowing robot and configured to detect radiation reflected by objects in the environment, and a controller configured to controllably direct radiation from the radiation source to scan the environment, and to vary at least one of an output power of the directed radiation and a scan rate of the directed radiation, as a function of detected radiation reflected from one or more of the synthetic surfaces. In the method the controller is configured to control the controller to vary the scan rate of the radiation source. Also included can be a modulator coupled to the radiation source and configured to modulate radiation emitted from the radiation source. The controller is configured to direct the modulator to vary the output power of the radiation source in response to detection of reflected radiation. The controller is configured to direct the modulator to vary a beam focus of the radiation source in response to detection of reflected radiation. The modulator scans a portion of a second scan at a scan speed different from at least a portion of the scan speed of a first scan. Positioning a plurality of synthetic surfaces comprises positioning the surfaces at locations bordering the environment. The controller scans the environment during a motion of the robot. The motion of the robot includes a grass cutting action.
In further implementations, an autonomous robot comprises a body configured to move over a surface, two driven wheels carried by the body and defining a transverse axis, with each wheel carried on a respective side of the body, a radiation source coupled to the autonomous robot, a detector coupled to the autonomous mowing robot and configured to detect radiation reflected by objects in the environment, and a controller configured to controllably direct radiation from the radiation source to scan the environment, and to vary at least one of an output power of the directed radiation and a scan rate of the directed radiation, as a function of detected radiation reflected from one or more of synthetic surfaces placed in the environment. In some embodiments, the controller is configured to vary the scan rate of the radiation source. A modulator coupled to the radiation source is configured to modulate radiation emitted from the radiation source. The controller is configured to direct the modulator to vary the output power of the radiation source in response to detection of reflected radiation. The controller is configured to direct the modulator to vary a beam focus of the radiation source in response to detection of reflected radiation. A blade is attached to the body. An odometer is in communication with the wheels, wherein the controller is further configured to compare the position of the robot resulting from the identified radiation to a position of the robot indicated by the odometer. The controller is further configured to drive the wheels so as to change a trajectory of the robot in response to determining the robot position. The radiation source scans during a motion of the robot.
In further implementations, a location estimation system for use with an autonomous lawn mowing robot comprises a plurality of reflective surfaces positioned with respect to a mowable space in an environment, a radiation source coupled to the lawn mowing robot, a detector coupled to the lawn mowing robot and configured to detect radiation reflected by objects in the environment and radiation reflected by the plurality of reflective surfaces, and a processor configured to: identify a signal received by the detector as being associated with one of the plurality of reflective surfaces, compare signals received by the detector at locations near the identified signal to determine environmental characteristics based on radiation reflected by objects in the environment, and determine which of the plurality of reflective surfaces generated the signal received by the detector based on the comparison.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.
Like reference symbols in the various drawings indicate like elements.
Referring to
A data processor or controller 150 having a memory 151 is attached to the robot body 100 and communicates with and controls a radiation source 180 also attached to the robot body 100. The radiation source 180 can one of several types of radiation used for robot navigation, such as a lidar (light or laser) source, or a radar source. Laser or radar sources are particularly advantageously suited for use in the navigation embodiments described herein. In some examples, the radiation source is attached to the robot on a rotating platform or other scanner that is configured to cause the beam to scan about the environment in predetermined angular increments (e.g., one degree increments).
The controller 150 also communicates with a modulator 185 coupled to the radiation source. The modulator 185 modulates the radiation emitted from the radiation source 180. For example, the modulator 185 can modify the beam focus, the beam power, and/or range of the beam of radiation supplied by the radiation source 180 and emitted by the robot lawnmower 10. The radiation source 180, modulator 185, and controller 150 are also in communication with a radiation detector or receiver 190 that detects incoming radiation incident on the robot lawnmower 10. As shown in
The controller 150 also communicates with the other systems of the robot, e.g., the drive system 140, the surface sensor, and the surface treater 120. The robot lawnmower 10 can also include a user interface system 170, which allows a human user to see messages indicating states of the robot lawnmower 10. The user interface system 170 is also in communication with the controller 150. In some embodiments, the user interface system 170 is not located on the robot body 100. Instead, the user interface system 170 can be a standalone unit, separate from the robot body 100. In other implementations, the user interface system can be integrated into another device, such as via a software located on a user's cell phone, tablet, or other device and the robot can communicate with the user interface via a Wi-Fi signal over the internet.
Referring to
Each boundary marker 205, 210, 215 is positioned at a location, and situated so as to be detected by the robot lawnmower 10 as the robot lawnmower 10 navigates the lawn 20. To determine its position on the lawn 20, as shown schematically in
As shown in
In other implementations, boundary markers 205, 210, 215 can be configured as optical corner reflectors, or corner cubes. An optical corner reflector is a retroreflector consisting of three mutually perpendicular intersecting flat surfaces. Each surface reflects incident radiation emitted by emitters 180, 194 on the robot lawnmower 10 back directly towards the source, e.g., to be detected by the detectors 190, 196. Each incoming ray incident on the cube is reflected three times, once by each surface, which results in a reversal of direction. The three intersecting surfaces often have square shapes, and can be made of three-sided glass prisms.
In general, the pose of the robot lawnmower 10 can be determined based on the signals reflected by the boundary markers 205, 210, 215. More particularly, the robot lawnmower 10 sends a signal (e.g., a laser signal) that is reflected by one of the boundary markers. The robot lawnmower 10 can determine the angle between the robot lawnmower 10 relative to the boundary marker based on the location at which the signal is received. Additionally, the robot lawnmower 10 can determine the distance between the robot lawnmower 10 and the boundary marker 200 based on the time-of-flight between the sending of the signal and the receipt of the reflected signal. Thus, based on the information from multiple boundary markers 200, the robot lawnmower's pose can be determined by trilaterating based on received range/heading information from each of the boundary markers. In general, trilateration is the process of determining absolute or relative locations of points by measurement of distances, using the geometry of circles, spheres or triangles. In one example, trilaterating can be based on a least squares algorithm using the distance/time-of-flight measurements. In another example, time-of-flight can be measured indirectly by measuring the phase shift between the signal and the receipt of the reflected signal.
In general, reflective beacons do not generate a signal that is uniquely identifiable—e.g., the signal from one beacon is not uniquely identifiable as originating from that beacon. However, if the system were to be able to distinguish between the signals generated by the beacons, this information could be used to determine the pose of the robot lawn mower. In some examples, the beacons can be configured to return a unique which is distinguishable from signals from other boundary markers. In some implementations, the unique signal can be implemented with a passive retroreflector, by e.g., a unique size, shape, or pattern to the boundary marker 200 or dock 12 that encodes the particular boundary marker. The unique signal permits the robot lawnmower 10 to uniquely identify the signal as being associated with a particular beacon.
In another example, signals and information about the environment surrounding the beacon can be used to uniquely identify a particular beacon. More particularly, the environment around each of the beacons will differ and therefore generate a different reflective signal. For example, if one beacon is located near a tree, the tree will provide a weaker reflected signal at a distance relative to the beacon. Thus, a scan matching process can use the combination of the signal reflected from the beacon and the signals reflected from environmental objects to uniquely identify the beacon.
Scan matching involves taking and storing scan data of the environment. In some implementations, the location determination performed by the robot lawnmower 10 includes performing a scan match on three or more adjacent boundary markers 200, where each of the three or more boundary markers 200 are individually identifiable by adjacent scan match data. More particularly, because the beacons are passive, the signal reflected from the beacon itself is not distinguishable from a signal reflected from another beacon. By combining the reflected signal from the beacon with a reflective signature of a scan around (e.g., 5 degrees on either side, 3 feet on either side) of the beacon, the beacon can be uniquely identified relative to the other beacons. For example,
As each scan performed by the robot at differing locations on the lawn 20 will result in signature reflections of varying strength, the robot lawnmower can determine its position or pose of the robot on the lawn 20 by matching the current travel path scan with stored travel path scans contained in the robot's memory 151.
At the pose P2 of the robot lawnmower 10 in
To increase computational efficiency, the robot lawnmower can use a library of signatures relating specifically to the boundary markers. The robot lawnmower 10 can scan the environment near the reflective boundary markers and identify specific features in the immediate vicinity of the particular boundary marker, 205, 210, 215, 12. This narrow scan range gives a partial fingerprint that is easier to match. To reduce computational cost the robot lawnmower 10 could be configured to scan a reduced signature library, or more quickly scan a library of stored locations using this specific signature.
In some implementations, each of the retroreflectors can have a unique signature based on a unique size, shape, or pattern to the reflector that encodes the particular boundary marker. The unique signal permits the robot lawnmower 10 to uniquely identify the signal and thus the location and orientation of dock 12. Based on identifying this unique retroreflector signal, the processor of the robot lawnmower 10 can select only the scans in memory containing the unique signal. In further implementations, the processor of the robot lawnmower can combine position information given by the unique signal and a scan match of the environment.
To perform scan matching, the robot lawnmower 10 can first “learn” the environment by taking scans of the entire lawn 20. In a learning mode, the robot can navigate the lawn, and record the fingerprint signature of radiation received at different poses on the lawn 20 to build a radiative signature library. A user may direct the robot lawnmower 10 during this learning mode. Alternatively, the robot lawnmower 10 can navigate and scan the environment autonomously, and build a library of stored scans for later retrieval. In some implementations, the robot lawnmower 10 can continuously update the stored scan library during mowing operations. This technique can account for variations in the signature scans due to changes in reflections caused by changes of objects in the environment over time.
Referring to
The triangulation techniques discussed above can potentially incur multipath error. Multipath error can occur due to objects placed within the environment. For example, radiation emitted from the robot lawnmower 10 could be reflected of objects such as a car, a bicycle, and then be incident on the robot lawnmower 10 as a false return signal. To account for these inaccuracies, robot lawnmower can be configured to perform both the query of the boundary markers 200 as well as a scan match at each pose of the robot lawnmower 10. The scan match can confirm that the reflected signal is from a boundary marker as opposed to another environmental feature.
Further embodiments of this disclosure relate to variable control of parameters of radiation, 196. In a preferred embodiment, the radiation source is a laser configured to spin about an axis and is connected to a controller that modulates the spin rate and/or power level of the laser. However, the control methods described can apply to either or both of laser radiation and radar radiation. The methods are designed to work in conjunction with retroreflectors, radar reflectors, or other reflective boundary markers 200. In particular, the arc length between the laser signals, the emitted signal strength, or both can be modified.
Signal is proportional to the inverse of the radius squared, where the radius is the distance between the robot lawnmower 10 and the object detected (e.g., the boundary marker 200). Thus, both strong and weak signals are incident on the detectors 190, 196, depending on the distance to the reflected surface. Radius also impacts the noise of the incoming signal, e.g., closer signals are typically less noisy. In addition, the surface upon which the light is incident can reflect a varying amount of the signal. For example, the signals reflected by retroreflective beacons are extremely strong, and can be much higher than signals due to other objects in the environment such as trees or bricks. Thus, a high detected signal can indicate the position of a retroreflector. To account for these variations in signal strength, the robot lawnmower can adjust the radiation emitted. Additionally, if the radiation source is configured to generate a signal at a predefined frequency, the likelihood of receiving a reflection from an item located nearer to the robot is greater than the likelihood of receiving a reflection from an item located further away because as the distance from the robot increases so does the arc length between the signals.
In one implementation, the robot lawnmower 10 does a first sweep to scan the lawn 20 at a first rate, and stores the locations of higher signal and/or reduced noise as areas of interest. The robot lawnmower 10 then performs a second sweep to scan the lawn during which the robot slows the scan and focuses on the detected areas of interest determined by the increase in signal strength on the first sweep. More particularly, the controller issues a command to cause the laser or radar to rotate at a slower rate in the determined areas of interest such that a greater amount of information can be generated in those areas (e.g., the scan can include pings of the laser at smaller degree increments such as every 0.2-0.75 degrees as opposed to every one degree). In some examples, a ratio of the degree increments for the pings in the less focused (faster spin rate) scan versus the more focused (slower spin rate) scan can be between 0.1 and 0.8, for example, between 0.25 and 0.5. To ensure the robot is capturing the reflectors, the robot lawnmower 10 slows the scan around the expected positions of the boundary markers 200 in subsequent scans. The slower the rotation/spin rate, the more likely it is to see a small retroreflector from a further distance (e.g., in
In
In some examples, the robot can alternate between fast and slow spin rates. For example, the robot can perform one rotation at a first spin rate to gather detailed information about the robot location. The robot could then operate using a higher spin rate for the subsequent 5-10 rotations. In another example, the spin rate of the laser could be modified based on the proximity to the edge of the mowable space. For example, as the robot lawn mower approaches the boundary of the mowable space the speed at which the mower is propelled could be reduced. In addition, the speed at which the laser rotates could be reduced to gather a greater resolution in the data used to localize the robot lawn mower.
In a further embodiment, in
Referring to
The robot lawnmower 10 can perform the positioning initial sweep at predetermined time periods or upon the detection of a beacon outside the slow spin rate zone. In some examples, a ratio of the fast spin rate to the slower spin rate can be between 2:1 and 5:1, e.g., about 2:1, about 3:1, about 4:1, about 5:1.
In some additional examples, rather than vary the spin rate during a particular rotation, the controller can cause the laser to spin with the spin rate alternating between the faster and slower spin rates after a set number of rotations. This can allow the robot to gather more information and potentially determine the robot's pose with greater detail during a slow spin rate scan while tracking the robot and any movements on a basis that is updated more frequently using the higher spin rate scans.
In other embodiments, to optimize object detection, the power level or beam focus of the radiation emitted from robot lawnmower 10 can be modulated. Generally, lower power is preferable for identifying objects nearby than far away and high power is better for detecting signals from objects further away. High power output results in noise on close obstacles, while seeing objects further away clearly. If operating on low power alone, the robot lawnmower may not be able to detect further away objects. To try and capture the advantages of both power levels (while minimizing the disadvantages) the robot lawnmower 10 can be configured to change the power level of the emitted radiation on various positions during a sweep.
If strongly reflecting targets are close to the robot (at a given position) and the boundary markers 200 are farther away, the robot lawnmower 10 can use the received signal strength for that beacon to change the power level up or down. For example, the robot may increase the power level of the signal where the boundary marker 200 is expected to be, or has previously determined to be located. If the return signal strength is low, the robot will increase the power in an attempt to detect the boundary marker 200 that has been drowned out by the closer (and therefore higher signal) reflecting target.
Referring to
Referring to
In some examples, a controller 150 in communication with the laser or other radiation source is configured to perform scans at alternating power levels. For example, rather than vary the power level during a particular rotation, the controller 150 can cause the laser to alternate between the two power levels after a set number of rotations. This can allow the robot to gather more information and potentially determine the robot's pose with greater detail because both nearby and further away objects will be located based on the two different scan power levels.
Retroreflector surfaces such as boundary markers generally have a much stronger signal than do environmental objects. To account for the differing strength of detected signals resulting from different object types, as well as from distance, different detection schemes are possible. For example, detector 190 on the front of the robot body can be composed of two different detectors. Similarly, detector 196 on the rear of the robot body 100 can actually be composed of two detectors Each pair of detectors can include one detector configured to detect lower power signals and one detector configured to detect higher power signals. In one implementation, filtered glass placed in front of detectors can attenuate the signal incident on the detectors making it more tuned to detecting high signals (e.g., returned from the boundary markers 200).
Detectors 193, 197 can be specifically tuned to detect boundary markers 200 and thus dedicated to determining robot positioning within the environment, while detectors 190, 194 can be tuned to detect nearby obstacles within the environment. The front detectors 193 and 190 could be stacked on top each other, as can the rear detectors 196, 197.
In further implementations, the front emitter 190 can actually be configured as two emitters 190, 191. Each emitter can be specially tuned to emit a high or lower power level, rather than modifying a single emitter to change its power. Similarly, the rear emitter 194 can actually be configured as two emitters 194, 195.
In other implementations, a single detector on the front 190 and back 196 can be used. The controller 150 can adjust the gain up and down in coordination with the expected strength of the detected signals.
One variation which can be used with embodiments including laser radiation accounts for terrain variations that can cause robot lawnmower 10 to change its pitch, i.e., tilt the robot body 100 up and down, as the robot lawnmower 10 traverses the lawn 20. These variations can make the laser miss the boundary markers by looking too high or too low. Additionally, laser signals are typically emitted as discrete signals, which might miss a boundary marker if the laser has positionally scanned by the boundary marker between successive laser pulses. To increase the likelihood of the emitted laser beam encountering a boundary marker, the laser signal can be fanned out into a plane.
Referring to
In an alternate embodiment, referring to
Referring to
While this specification contains many specifics, these should not be construed as limitations on the scope of the disclosure or of what may be claimed, but rather as descriptions of features specific to particular implementations of the disclosure. Certain features that are described in this specification in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.
Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multi-tasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Accordingly, other embodiments are within the scope of the following claims.
Number | Name | Date | Kind |
---|---|---|---|
2751030 | Null | Jun 1956 | A |
3128840 | Barrett | Apr 1964 | A |
3385041 | Douglas | May 1968 | A |
3457575 | Bienek | Jul 1969 | A |
3550714 | Bellinger | Dec 1970 | A |
3674316 | De Brey | Jul 1972 | A |
3924389 | Kita | Dec 1975 | A |
3937174 | Haaga | Feb 1976 | A |
3946543 | Templeton | Mar 1976 | A |
4119900 | Kremnitz | Oct 1978 | A |
4133404 | Griffin | Jan 1979 | A |
4163977 | Polstorff | Aug 1979 | A |
4306329 | Yokoi | Dec 1981 | A |
4369543 | Chen et al. | Jan 1983 | A |
4513469 | Godfrey et al. | Apr 1985 | A |
4545453 | Yoshimura et al. | Oct 1985 | A |
4556313 | Miller et al. | Dec 1985 | A |
4603753 | Yoshimura et al. | Aug 1986 | A |
4626995 | Lofgren et al. | Dec 1986 | A |
4674048 | Okumura | Jun 1987 | A |
4679152 | Perdue | Jul 1987 | A |
4696074 | Cavalli et al. | Sep 1987 | A |
4700301 | Dyke | Oct 1987 | A |
4700427 | Knepper | Oct 1987 | A |
4716621 | Zoni | Jan 1988 | A |
4733431 | Martin | Mar 1988 | A |
4756049 | Uehara | Jul 1988 | A |
4767237 | Cosman et al. | Aug 1988 | A |
4777416 | George et al. | Oct 1988 | A |
4782550 | Jacobs | Nov 1988 | A |
4796198 | Boultinghouse et al. | Jan 1989 | A |
4811228 | Hyyppa | Mar 1989 | A |
4854000 | Takimoto | Aug 1989 | A |
4887415 | Martin | Dec 1989 | A |
4893025 | Lee | Jan 1990 | A |
4909024 | Jones et al. | Mar 1990 | A |
4912643 | Beirne | Mar 1990 | A |
4918441 | Bohman | Apr 1990 | A |
4919224 | Shyu et al. | Apr 1990 | A |
4933864 | Evans et al. | Jun 1990 | A |
4962453 | Pong et al. | Oct 1990 | A |
4974283 | Holsten et al. | Dec 1990 | A |
5002145 | Waqkaumi et al. | Mar 1991 | A |
5017415 | Cosman et al. | May 1991 | A |
5086535 | Grossmeyer et al. | Feb 1992 | A |
5093955 | Blehert et al. | Mar 1992 | A |
5109566 | Kobayashi et al. | May 1992 | A |
5142985 | Stearns et al. | Sep 1992 | A |
5163202 | Kawakami et al. | Nov 1992 | A |
5163273 | Wojtkowski et al. | Nov 1992 | A |
5165064 | Mattaboni | Nov 1992 | A |
5204814 | Noonan et al. | Apr 1993 | A |
5208521 | Aoyama | May 1993 | A |
5216777 | Moro et al. | Jun 1993 | A |
5239720 | Wood et al. | Aug 1993 | A |
5261139 | Lewis | Nov 1993 | A |
5279672 | Belker et al. | Jan 1994 | A |
5284522 | Kobayashi et al. | Feb 1994 | A |
5293955 | Lee | Mar 1994 | A |
5303448 | Hennessey et al. | Apr 1994 | A |
5319828 | Waldhauser et al. | Jun 1994 | A |
5321614 | Ashworth | Jun 1994 | A |
5324948 | Dudar et al. | Jun 1994 | A |
5341540 | Soupert et al. | Aug 1994 | A |
5353224 | Lee et al. | Oct 1994 | A |
5369347 | Yoo | Nov 1994 | A |
5410479 | Coker | Apr 1995 | A |
5438721 | Pahno et al. | Aug 1995 | A |
5440216 | Kim | Aug 1995 | A |
5444965 | Colens | Aug 1995 | A |
5446356 | Kim | Aug 1995 | A |
5454129 | Kell | Oct 1995 | A |
5455982 | Armstrong et al. | Oct 1995 | A |
5465525 | Mifune et al. | Nov 1995 | A |
5467273 | Faibish | Nov 1995 | A |
5497529 | Boesi | Mar 1996 | A |
5507067 | Hoekstra et al. | Apr 1996 | A |
5515572 | Hoekstra et al. | May 1996 | A |
5528888 | Miyamoto et al. | Jun 1996 | A |
5534762 | Kim | Jul 1996 | A |
5537017 | Feiten et al. | Jul 1996 | A |
5539953 | Kurz | Jul 1996 | A |
5542146 | Hoekstra et al. | Aug 1996 | A |
5548511 | Bancroft | Aug 1996 | A |
5553349 | Kilstrom et al. | Sep 1996 | A |
5555587 | Guha | Sep 1996 | A |
5560077 | Crotchett | Oct 1996 | A |
5568589 | Hwang | Oct 1996 | A |
5611106 | Wulff | Mar 1997 | A |
5611108 | Knowlton et al. | Mar 1997 | A |
5613261 | Kawakami et al. | 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 |
5650702 | Azumi | Jul 1997 | A |
5652489 | Kawakami | Jul 1997 | A |
5682213 | Schmutz | Oct 1997 | A |
5682313 | Edlund et al. | Oct 1997 | A |
5682839 | Grimsley et al. | Nov 1997 | A |
5709007 | Chiang | Jan 1998 | A |
5761762 | Kubo et al. | Jun 1998 | A |
5781960 | Kilstrom et al. | Jul 1998 | A |
5787545 | Colens | Aug 1998 | A |
5794297 | Muta | Aug 1998 | A |
5812267 | Everett et al. | Sep 1998 | A |
5819008 | Asama et al. | Oct 1998 | A |
5825981 | Matsuda | Oct 1998 | A |
5839156 | Park et al. | Nov 1998 | A |
5841259 | Kim et al. | Nov 1998 | A |
5867800 | Leif | Feb 1999 | A |
5916111 | Colens | Jun 1999 | A |
5926909 | McGee | Jul 1999 | A |
5935179 | Kleiner 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 |
5959423 | Nakanishi et al. | Sep 1999 | A |
5974348 | Rocks | Oct 1999 | A |
6009358 | Angott et al. | Dec 1999 | A |
6041471 | Charkey et al. | Mar 2000 | A |
6049745 | Douglas et al. | Apr 2000 | A |
6073427 | Nichols | Jun 2000 | A |
6076025 | Ueno et al. | Jun 2000 | A |
6076227 | Schalig et al. | Jun 2000 | A |
6108067 | Hanseder | Aug 2000 | A |
6108076 | Hanseder | Aug 2000 | A |
6112143 | Allen et al. | Aug 2000 | A |
6124694 | Bancroft et al. | Sep 2000 | A |
6133730 | Winn | Oct 2000 | A |
6140146 | Brady et al. | Oct 2000 | A |
6166706 | Gallagher et al. | Dec 2000 | A |
6226830 | Hendriks et al. | May 2001 | B1 |
6240342 | Fiegert et al. | May 2001 | B1 |
6255793 | Peless et al. | Jul 2001 | B1 |
6259979 | Holmquist | Jul 2001 | B1 |
6285930 | Dickson et al. | Sep 2001 | B1 |
6300737 | Bergvall et al. | Oct 2001 | B1 |
D451931 | Abramson et al. | Dec 2001 | S |
6339735 | Peless et al. | Jan 2002 | B1 |
6374155 | Wallach et al. | Apr 2002 | B1 |
6385515 | Dickson et al. | May 2002 | B1 |
6408226 | Byrne et al. | Jun 2002 | B1 |
6417641 | Peless et al. | Jul 2002 | B2 |
6438456 | Feddema et al. | Aug 2002 | B1 |
6442476 | Poropat | Aug 2002 | B1 |
6443509 | Levin et al. | Sep 2002 | B1 |
6444003 | Sutcliffe | Sep 2002 | B1 |
6463368 | Feiten et al. | Oct 2002 | B1 |
6465982 | Bergvall et al. | Oct 2002 | B1 |
6493613 | Peless et al. | Dec 2002 | B2 |
6496754 | Song et al. | Dec 2002 | B2 |
6496755 | Wallach et al. | Dec 2002 | B2 |
6507773 | Parker et al. | Jan 2003 | B2 |
6525509 | Petersson et al. | Feb 2003 | B1 |
6532404 | Colens | Mar 2003 | B2 |
6535793 | Allard | Mar 2003 | B2 |
6548982 | Papanikolopoulos et al. | Apr 2003 | B1 |
6556598 | Angott | Apr 2003 | B1 |
6571415 | Gerber et al. | Jun 2003 | B2 |
6574536 | Kawagoe et al. | Jun 2003 | B1 |
6580246 | Jacobs | Jun 2003 | B2 |
6580978 | McTamaney | Jun 2003 | B1 |
6584376 | Kommer | Jun 2003 | B1 |
6586908 | Petersson et al. | Jul 2003 | B2 |
6594844 | Jones | Jul 2003 | B2 |
6604022 | Parker | 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 |
6658693 | Reed | Dec 2003 | B1 |
6661239 | Ozik | Dec 2003 | B1 |
6671592 | Bisset et al. | Dec 2003 | B1 |
6690134 | Jones et al. | Feb 2004 | B1 |
6741054 | Koselka et al. | May 2004 | B2 |
6748297 | Song et al. | Jun 2004 | B2 |
6764373 | Osawa et al. | Jul 2004 | B1 |
6781338 | Jones et al. | Aug 2004 | B2 |
6809490 | Jones et al. | Oct 2004 | B2 |
6830120 | Yashima et al. | Dec 2004 | B1 |
6841963 | Song et al. | Jan 2005 | B2 |
6845297 | Allard | Jan 2005 | B2 |
6850024 | Peless et al. | Feb 2005 | B2 |
6870792 | Chiappetta | Mar 2005 | B2 |
6883201 | Jones et al. | Apr 2005 | B2 |
6885912 | Peless et al. | Apr 2005 | B2 |
6901624 | Mori et al. | Jun 2005 | B2 |
D510066 | Hickey et al. | Sep 2005 | S |
6938298 | Aasen | Sep 2005 | B2 |
6940291 | Ozik | Sep 2005 | B1 |
6956348 | Landry et al. | Oct 2005 | B2 |
6971140 | Kim | Dec 2005 | B2 |
6984952 | Peless et al. | Jan 2006 | B2 |
6999850 | McDonald | Feb 2006 | B2 |
7024278 | Chiapetta et al. | Apr 2006 | B2 |
7069124 | Whittaker et al. | Jun 2006 | B1 |
7085624 | Aldred et al. | Aug 2006 | B2 |
7155309 | Peless et al. | Dec 2006 | B2 |
7203576 | Wilson et al. | Apr 2007 | B1 |
7206677 | Hulden | Apr 2007 | B2 |
D559867 | Abramson | Jan 2008 | S |
7349759 | Peless et al. | Mar 2008 | B2 |
D573610 | Abramson | Jul 2008 | S |
7441392 | Lilliestielke et al. | Oct 2008 | B2 |
7481036 | Lilliestielke et al. | Jan 2009 | B2 |
7525287 | Miyashita et al. | Apr 2009 | B2 |
7729801 | Abramson | Jun 2010 | B2 |
8046103 | Abramson et al. | Oct 2011 | B2 |
8069639 | Fancher | Dec 2011 | B2 |
D652431 | Naslund | Jan 2012 | S |
D656163 | Johansson et al. | Mar 2012 | S |
8136333 | Levin et al. | Mar 2012 | B1 |
8306659 | Abramson et al. | Nov 2012 | B2 |
8413616 | Bergquist | Apr 2013 | B2 |
8532822 | Abramson et al. | Sep 2013 | B2 |
8634960 | Sandin et al. | Jan 2014 | B2 |
8635841 | Fiser et al. | Jan 2014 | B2 |
8767190 | Hall | Jul 2014 | B2 |
8781627 | Sandin et al. | Jul 2014 | B2 |
8868237 | Sandin et al. | Oct 2014 | B2 |
8930127 | Shimshoni | Jan 2015 | B2 |
8954193 | Sandin et al. | Feb 2015 | B2 |
9043952 | Sandin et al. | Jun 2015 | B2 |
9043953 | Sandin et al. | Jun 2015 | B2 |
20010022506 | Peless et al. | Sep 2001 | A1 |
20010047231 | Peless et al. | Nov 2001 | A1 |
20020011813 | Koselka et al. | Jan 2002 | A1 |
20020015521 | Kim | Feb 2002 | A1 |
20020016649 | Jones | Feb 2002 | A1 |
20020120364 | Colens | Aug 2002 | A1 |
20020140393 | Peless et al. | Oct 2002 | A1 |
20020156556 | Ruffner | Oct 2002 | A1 |
20020160845 | Simonsen | Oct 2002 | A1 |
20020173877 | Zweig | Nov 2002 | A1 |
20030019071 | Field et al. | Jan 2003 | A1 |
20030023356 | Keable | Jan 2003 | A1 |
20030025472 | Jones et al. | Feb 2003 | A1 |
20030055337 | Lin | Mar 2003 | A1 |
20030060928 | Abramson et al. | Mar 2003 | A1 |
20030120389 | Abramson et al. | Jun 2003 | A1 |
20030137268 | Papanikolopoulos et al. | Jul 2003 | A1 |
20030182914 | Shibata et al. | Oct 2003 | A1 |
20030192144 | Song et al. | Oct 2003 | A1 |
20030208304 | Peless et al. | Nov 2003 | A1 |
20030216834 | Allard | Nov 2003 | A1 |
20030233177 | Johnson et al. | Dec 2003 | A1 |
20030234325 | Marino et al. | Dec 2003 | A1 |
20040020000 | Jones | Feb 2004 | A1 |
20040030448 | Solomon | Feb 2004 | A1 |
20040030449 | Solomon | Feb 2004 | A1 |
20040030450 | Solomon | Feb 2004 | A1 |
20040030571 | Solomon | Feb 2004 | A1 |
20040031113 | Wosewick et al. | Feb 2004 | A1 |
20040036618 | Ku et al. | Feb 2004 | A1 |
20040049877 | Jones et al. | Mar 2004 | A1 |
20040068351 | Solomon | Apr 2004 | A1 |
20040068415 | Solomon | Apr 2004 | A1 |
20040068416 | Solomon | Apr 2004 | A1 |
20040076324 | Burl et al. | Apr 2004 | A1 |
20040088079 | Lavarec et al. | May 2004 | A1 |
20040111184 | Chiappetta et al. | Jun 2004 | A1 |
20040111196 | Dean | Jun 2004 | A1 |
20040134336 | Solomon | Jul 2004 | A1 |
20040134337 | Solomon | Jul 2004 | A1 |
20040156541 | Jeon et al. | Aug 2004 | A1 |
20040158357 | Lee et al. | Aug 2004 | A1 |
20040187457 | Colens | Sep 2004 | A1 |
20040200505 | Taylor et al. | Oct 2004 | A1 |
20040204792 | Taylor et al. | Oct 2004 | A1 |
20040211444 | Taylor et al. | Oct 2004 | A1 |
20040220000 | Falone | Nov 2004 | A1 |
20040236468 | Taylor et al. | Nov 2004 | A1 |
20040244138 | Taylor et al. | Dec 2004 | A1 |
20050000543 | Taylor et al. | Jan 2005 | A1 |
20050007057 | Peless et al. | Jan 2005 | A1 |
20050010331 | Taylor et al. | Jan 2005 | A1 |
20050020374 | Wang | Jan 2005 | A1 |
20050097952 | Steph | May 2005 | A1 |
20050108999 | Bucher | May 2005 | A1 |
20050113990 | Peless et al. | May 2005 | A1 |
20050156562 | Cohen et al. | Jul 2005 | A1 |
20050204717 | Colens | Sep 2005 | A1 |
20050251292 | Casey et al. | Nov 2005 | A1 |
20050278094 | Swinbanks et al. | Dec 2005 | A1 |
20050287038 | Dubrovsky et al. | Dec 2005 | A1 |
20060293794 | Harwig et al. | Dec 2006 | A1 |
20070016328 | Ziegler et al. | Jan 2007 | A1 |
20070142964 | Abramson | Jun 2007 | A1 |
20070150109 | Peless et al. | Jun 2007 | A1 |
20080039974 | Sandin | Feb 2008 | A1 |
20080097645 | Abramson et al. | Apr 2008 | A1 |
20080167753 | Peless et al. | Jul 2008 | A1 |
20080183349 | Abramson et al. | Jul 2008 | A1 |
20090254218 | Sandin et al. | Oct 2009 | A1 |
20100059000 | Bergquist | Mar 2010 | A1 |
20100102525 | Fancher | Apr 2010 | A1 |
20100256908 | Shimshoni | Oct 2010 | A1 |
20110130875 | Abramson | Jun 2011 | A1 |
20110234153 | Abramson | Sep 2011 | A1 |
20120041594 | Abramson et al. | Feb 2012 | A1 |
20120063269 | Chung | Mar 2012 | A1 |
20120085820 | Morgan | Apr 2012 | A1 |
20120226381 | Abramson et al. | Sep 2012 | A1 |
20130006419 | Bergstrom et al. | Jan 2013 | A1 |
20130030609 | Jagenstedt | Jan 2013 | A1 |
20130066484 | Markusson et al. | Mar 2013 | A1 |
20130076304 | Andersson et al. | Mar 2013 | A1 |
20130110322 | Jagenstedt et al. | May 2013 | A1 |
20130152538 | Fiser et al. | Jun 2013 | A1 |
20130184924 | Jagenstedt et al. | Jul 2013 | A1 |
20130249179 | Burns | Sep 2013 | A1 |
20130274920 | Abramson et al. | Oct 2013 | A1 |
20140102061 | Sandin et al. | Apr 2014 | A1 |
20140102062 | Sandin et al. | Apr 2014 | A1 |
20140117892 | Coates | May 2014 | A1 |
20140247116 | Davidson | Sep 2014 | A1 |
20150006015 | Sandin et al. | Jan 2015 | A1 |
20160026185 | Smith | Jan 2016 | A1 |
Number | Date | Country |
---|---|---|
19932552 | Feb 2000 | DE |
0792726 | Sep 1997 | EP |
0774702 | Oct 2001 | EP |
1331537 | Jul 2003 | EP |
1704766 | Dec 2008 | EP |
2828589 | Feb 2003 | FR |
2142447 | Jan 1985 | GB |
2283838 | May 1995 | GB |
2382157 | May 2003 | GB |
62120510 | Jun 1987 | JP |
62154008 | Jul 1987 | JP |
63183032 | Jul 1988 | JP |
63241610 | Oct 1988 | JP |
2-6312 | Jan 1990 | JP |
3051023 | Mar 1991 | JP |
04320612 | Nov 1992 | JP |
06327598 | Nov 1994 | JP |
07129239 | May 1995 | JP |
7295636 | Nov 1995 | JP |
816776 | Jan 1996 | JP |
08089451 | Apr 1996 | JP |
8152916 | Jun 1996 | JP |
09179625 | Jul 1997 | JP |
9185410 | Jul 1997 | JP |
11-508810 | Aug 1999 | JP |
11-510935 | Sep 1999 | JP |
2001-258807 | Sep 2001 | JP |
2001-275908 | Oct 2001 | JP |
2001-525567 | Dec 2001 | JP |
2002078650 | Mar 2002 | JP |
2002-204768 | Jul 2002 | JP |
2002-532178 | Oct 2002 | JP |
3356170 | Oct 2002 | JP |
2002-323925 | Nov 2002 | JP |
3375843 | Nov 2002 | JP |
2002-355206 | Dec 2002 | JP |
2002-360471 | Dec 2002 | JP |
2002-360482 | Dec 2002 | JP |
2003005296 | Jan 2003 | JP |
2003010076 | Jan 2003 | JP |
2003-505127 | Feb 2003 | JP |
2003036116 | Feb 2003 | JP |
2003038401 | Feb 2003 | JP |
2003038402 | Feb 2003 | JP |
2003061882 | Mar 2003 | JP |
2003-310489 | Nov 2003 | JP |
9526512 | Oct 1995 | WO |
9740734 | Nov 1997 | WO |
9741451 | Nov 1997 | WO |
9853456 | Nov 1998 | WO |
9916078 | Apr 1999 | WO |
9928800 | Jun 1999 | WO |
9938056 | Jul 1999 | WO |
9938237 | Jul 1999 | WO |
9959042 | Nov 1999 | WO |
0004430 | Jan 2000 | WO |
0036962 | Jun 2000 | WO |
0038026 | Jun 2000 | WO |
0038029 | Jun 2000 | WO |
0078410 | Dec 2000 | WO |
0106904 | Feb 2001 | WO |
0106905 | Feb 2001 | WO |
0239864 | May 2002 | WO |
0239868 | May 2002 | WO |
02058527 | Aug 2002 | WO |
02062194 | Aug 2002 | WO |
02067744 | Sep 2002 | WO |
02067745 | Sep 2002 | WO |
02074150 | Sep 2002 | WO |
02075356 | Sep 2002 | WO |
02075469 | Sep 2002 | WO |
02075470 | Sep 2002 | WO |
02101477 | Dec 2002 | WO |
03026474 | Apr 2003 | WO |
03040845 | May 2003 | WO |
03040846 | May 2003 | WO |
03065140 | Aug 2003 | WO |
2004004533 | Jan 2004 | WO |
2004006034 | Jan 2004 | WO |
2004058028 | Jul 2004 | WO |
2005055795 | Jun 2005 | WO |
2005077244 | Aug 2005 | WO |
2006068403 | Jun 2006 | WO |
Entry |
---|
E. Casanova, S. Quijada, J. Garcia-Bermejo and J. Gonzalez, “Microcontroller based system for 2D localization,” Mechatronics 15, 2005, pp. 1109-1126. |
Angle et al., U.S. Appl. No. 60/177,703, filed Jan. 24, 2000, available at http://portal.uspto.gov/external/portal/pair , accessed Jul. 11, 2012, 16 pages. |
Bohn et al. “Super-distributed RFID Tag Infrastructures,” Lecture Notes in Computer Science, Springer Verlag, Berlin, DE, vol. 3295, Nov. 11, 2004, pp. 1-12. |
Campbell et al., U.S. Appl. No. 60/741,442, filed Dec. 2, 2005, available at http://patentscope.wipo.int/search/docservicepdf—pct/id00000005206306.pdf, accessed Jul. 11, 2012, 130 pages. |
Casey et al., U.S. Appl. No. 60/582,992, filed Jun. 25, 2004, available at http://portal.uspto.gov/external/portal/pair, accessed Jul. 11, 2012, 24 pages. |
Caracciolo et al., “Trajectory Tracking Control of a Four-Wheel Differentially Driven Mobile Robot,” IEEE Int. Conf. Robotics and Automation, Detroit, MI, 1999, pp. 2632-2638. |
Domnitcheva “Smart Vacuum Cleaner—An Autonomous Location-Aware Cleaning Device,” Proceedings of the International Conference on Ubiquitous Computing, Sep. 10, 2004, pp. 1-2. |
Doty and Harrison, “Sweep Strategies for a Sensory-Driven, Behavior-Based Vacuum Cleaning Agent,” AAAI 1993 Fall Symposium Series, Instantiating Real-World Agents, Oct. 22-24, 1993, pp. 1-6. |
“Electrolux—Designed for the well-lived home (Welcome to the Electrolux Trilobite),” Retrieved from the Internet: URL<http://www.electroluxusa.com/node57.as[?currentURL=node142.asp%3F >. Accessed Mar. 2005, 2 pages. |
“eVac Robotic Vacuum,” S1727 Instruction Manual, Sharper Image Corp, Copyright 2004, 13 pages. |
Everyday Robots, “Everyday Robots: Reviews, Discussion and News for Consumers,” Aug. 2004, Retrieved from the Internet: URL<www.everydayrobots.com/index.php?option=content&task=view&id=9>, retrieved Sep. 2012, 4 pages. |
Evolution Robotics, “NorthStar—Low-cost Indoor Localization—How it Works,” E Evolution Robotics, 2005, 2 pages. |
Facts on Trilobite, webpage, Retrieved from the Internet: URL<http://trilobiteelectroluxse/presskit—en/model111335asp?print=yes&pressID=>, accessed Dec. 2003, 2 pages. |
Final Office Action issued in U.S. Appl. No. 11/688,225, dated Nov. 10, 2011, 45 pages. |
Gat, “Robust Low-Computation Sensor-driven Control for Task-Directed Navigation,” Proc of IEEE International Conference on Robotics and Automation, Sacramento, CA, Apr. 1991, pp. 2484-2489. |
Hicks and Hall, “A Survey of Robot Lawn Mowers”, http://www.robotics.uc.edu/papers/paper2000/lawnmower.pdf, 2000, 8 pages. |
Hitachi: News release: “The home cleaning robot of the autonomous movement type (experimental machine) is developed,” May 29, 2003, Retrieved from the Internet: URL<www.i4u.com./japanreleases/hitachirobot.htm>, retrieved Mar. 2005, 5 pages. |
International Preliminary Report on Patentability dated Sep. 23, 2008 from International Application No. PCT/US2007/064326, dated Sep. 23, 2008, 10 pages. |
International Preliminary Report on Patentability issued in International Application No. PCT/US2007/064323, dated Sep. 23, 2008, 10 pages. |
International Search Report and Written Opinion issued in PCT/US2007/064326, dated Jul. 17, 2008, 6 pages. |
International Search Report and Written Opinion issued in PCT/US2007/064323, dated Jun. 16, 2008, 14 pages. |
Invitation to Pay Additional Fees issued in International Application No. PCT/US2007/064326, dated Apr. 18, 2008, 9 pages. |
Kahney, “Wired News: Robot Vacs are in the House,” Jun. 2003, Retrieved from the Internet: URLwww.wired.com/news/technology/o.1282,59237,00.html, accessed Mar. 2005, 5 pages. |
Karcher “Karcher RoboCleaner RC 3000,” Retrieved from the Internet: URLwww.robocleaner.de/english/screen3.html, accessed Dec. 2003, 4 pages. |
Karcher USA, “RC3000 Robotic Cleaner,” 2005, Retrieved from the Internet: URL http://www.karcher-usa.com/showproducts.php?op=view prod¶m1=143¶m2=¶m3=, accessed Mar. 2005, 3 pages. |
Karcher, “Product Manual Download ‘Karch’,” available at www.karcher.com, 2004, 16 pages. |
Karcher, RC 3000 Cleaning Robot-User Manual Manufacturer: Alfred-Karcher GmbH & Co, Cleaning Systems, Alfred Karcher-Str 28-40, PO Box 160, D-71349 Winnenden, Germany, Dec. 2002, 8 pages. |
Kimura et al., “Stuck Evasion Control for Active Wheel Passive-Joint Snake-like Mobile Robot ‘Genbu’,” Proceedings of the 2004 IEEE International Conference on Robotics 8 Automation, New Orleans, LA, Apr. 2004, 6 pages. |
Kozlowski and Pazderski, “Modeling and Control of a 4-wheel Skid-steering Mobile Robot,” International J. of Applied Mathematics and Computer Science, 2004, 14(4):477-496. |
Koolvac Robotic Vacuum Cleaner Owner's Manual, Koolatron, 2004, 13 pages. |
Kubitz et al., “Application of radio frequency identification devices to support navigation of autonomous mobile robots” Vehicular Technology Conference, vol. 1, May 4, 1997, pp. 126-130. |
Matthies et al., “Detecting Water Hazards for Autonomous Off-Road Navigation,” Proceedings of SPIE Conference 5083: Unmanned Ground Vehicle Technology V, Orlando, FL, Apr. 2003, pp. 231-242. |
Morland,“Autonomous Lawnmower Control,” Downloaded from the internet at: http://cns.bu.edu/˜cjmorlan/robotics/lawnmower/report.pdf, Jul. 2002, 10 pages. |
Non-final Office Action issued in U.S. Appl. No. 11/688,213, dated Jan. 27, 2011, 27 pages. |
Non-final Office Action issued in U.S. Appl. No. 11/688,225, dated Feb. 24, 2011, 30 pages. |
Non-final Office Action issued in U.S. Appl. No. 12/488,094, dated Jan. 26, 2011, 25 pages. |
Non-final Office Action issued in U.S. Appl. No. 12/488,094, dated Jul. 28, 2011, 13 pages. |
On Robo, “Robot Reviews Samsung Robot Vacuum (VC-RP30W),” 2005, Retrieved from the Internet: URL www.onrobo.com/reviews/AT—Home/vacuum—cleaners/on00verb30rosam/index.htm, accessed Mar. 2005, 2 pages. |
“Put Your Roomba . . . On, Automatic” webpages: http://www.acomputeredge.com/roomba, accessed Apr. 2005, 3 pages. |
RoboMaid Sweeps Your Floors So You Won't Have to, the Official Site, Retrieved from the Internet: URLhttp://therobomaid.com/, accessed Mar. 2005, 2 pages. |
Robotic Vacuum Cleaner-Blue, Retrieved from the Internet: URL http://www.sharperimage.com/us/en/catalog/productview.jhtml?sku=S1727BLU, accessed Mar. 2005, 2 pages. |
Schofield, “Neither Master nor Slave—A Practical Study in the Development and Employment of Cleaning Robots,” Emerging Technologies and Factory Automation, 1999 Proceedings ETFA '99 1999 7th IEEE International Conference on Barcelona, Spain, Oct. 1999, pp. 1427-1434. |
TheRobotStore.com, “Friendly Robotics Robotic Vacuum RV400—The Robot Store,” www.therobotstore.com/s.nl/sc.9/category.-109/it.A/id.43/.f, accessed Apr. 2005, 1 page. |
Thrun, “Learning Occupancy Grid Maps With Forward Sensor Models,” Autonomous Robots 15, Sep. 1, 2003, 28 pages. |
Wigley, “The Electric Lawn”, in The American Lawn, Princeton Architectural Press New York with Canadian Centre for Architecture Montreal, 1999, pp. 155-195. |
“Zoombot Remote Controlled Vaccuum—RV-500 New Roomba 2,” eBay website: http://cgi.ebay.com/ws/eBayISAPI.dll?ViewItem&category=43526&item=4373497618&rd=1, accessed Apr. 2005, 7 pages. |
International Search Report and Written Opinion in International Application No. PCT/US2015/048270, dated Dec. 4, 2015, 12 pages. |
Number | Date | Country | |
---|---|---|---|
20160100521 A1 | Apr 2016 | US |