Experience-based roadmap for a robotic cleaning device

Information

  • Patent Grant
  • 10534367
  • Patent Number
    10,534,367
  • Date Filed
    Tuesday, December 16, 2014
    10 years ago
  • Date Issued
    Tuesday, January 14, 2020
    4 years ago
Abstract
A method of operating a robotic cleaning device over a surface to be cleaned. The method includes: registering roadmap nodes at intervals on the surface during cleaning, the roadmap nodes including positional information; and linking the roadmap nodes to form roadmap links in a roadmap graph, if the robotic cleaning device is driving directly from a previously registered roadmap node to a currently registered roadmap node. The roadmap links in the roadmap graph facilitate navigation of the robotic cleaning device.
Description

This application is a U.S. National Phase application of PCT International Application No. PCT/EP2014/077947, filed Dec. 16, 2014, which is incorporated by reference herein.


TECHNICAL FIELD

The invention relates to a robotic cleaning device and to a method of operating and navigating the robotic cleaning device by registering roadmap nodes when driving.


BACKGROUND

In many fields of technology, it is desirable to use robots with an autonomous behaviour such that they can freely move around a space without colliding with possible obstacles.


Robotic vacuum cleaners or robotic floor mops, further referred to as robotic cleaning devices, are known in the art and usually equipped with drive means in the form of one or more motors for moving the cleaner across a surface to be cleaned. The robotic cleaning devices may further be equipped with intelligence in the form of microprocessor(s) and navigation means for causing an autonomous behaviour such that the robotic vacuum cleaners can freely move around and clean a space in the form of e.g. a room. Thus, these prior art robotic cleaning devices have the capability of more or less autonomously vacuum clean or mop a room, in which furniture such as tables, chairs and other obstacles such as walls and stairs are located.


There are basically two categories of robotic cleaning devices known in the prior art; —the ones which clean a surface by random motion and the ones which navigate using various sensor data.


The robotic cleaning devices, which use a random motion also look randomly for the charger. These robotic cleaning devices navigate and clean by principle of contingency. Such robotic cleaning devices may comprise a collision sensor to avoid collisions when cleaning. Typically they have means to detect and locate the charger when they happen to pass it or when the charger comes into the field of view. This is obviously not a very efficient way of cleaning and navigating and may in particular not work very well for large surfaces or for complicated layouts.


The other type of prior art robotic cleaning devices, which navigate using sensor data deduced from the sensor data where they can safely drive without collisions with obstacles. As they make assumptions about their environment based on the sensor data, which is in most cases not complete, they run a high risk of getting stuck or lost. In addition, extracting data and thus making assumptions from the sensor data additionally requires expensive electronic components.


In some cases prior art robotic cleaning devices use a stroke method to clean, which means they drive back and forth stroke by stroke in order to clean a surface. When navigating such a prior robotic cleaning device from one room to another or back to the charger, the robotic cleaning device uses sensor data to navigate. The risk of colliding with obstacles is then comparably high, since such robotic cleaning devices are also forced to make assumptions based on the sensor data. This may slow down the robotic cleaning device and thus reduce the efficiency of the cleaning.


In other cases the robotic cleaning device may even get stuck without any battery power left because the distances it has to drive are too far and not properly planned.


SUMMARY

An object of the present invention is to provide a method of operating a robotic cleaning device that is robust and efficient.


It is advantageous to provide a robotic cleaning device comprising a processing unit or the like that is configured to perform the method in order to operate the robotic cleaning device accordingly.


The inventors have realized that it is possible to take advantage of the fact that a robotic cleaning device is moving eventually across an entire surface to be cleaned. Because the robotic cleaning device is eventually covering the entire surface and this many times during its operating life, it is possible to provide a robust and surprisingly efficient method to enhance the safety and efficiency of the navigation and cleaning performed by the robotic cleaning device.


Disclosed herein is a method of operating a robotic cleaning device over a surface to be cleaned comprising the steps of:


registering roadmap nodes at intervals on the surface during cleaning, said roadmap nodes comprising positional information;


linking the roadmap nodes to form roadmap links in a roadmap graph, if the robotic cleaning device is driving directly from a previously registered roadmap node to a currently registered roadmap node, whereby the roadmap links in the roadmap graph may facilitate navigation of the robotic cleaning device.


The roadmap links may form a sequence, whereby this sequence may be continuous or not. Such a sequence forms a path, which the robotic cleaning device can reuse and follow at a later stage, for example to transport itself from one point to another or for navigating from an arbitrary position back to the charger.


The above described method takes advantages of the fact that the robotic cleaning device is navigating over the entire surface to be cleaned. Eventually the surface is virtually covered with roadmap nodes that are linked together. The robotic cleaning device thus knows exactly where it can safely drive without colliding with an obstacle. In other words, because the robotic cleaning device continuously registers roadmap nodes there will always be a possibility for the robotic cleaning device to find an obstacle-free path or sequence from its current position to any position where it has been before.


The roadmap nodes may be virtual roadmap nodes, registered in the memory of the robotic cleaning device.


In the above, the term driving directly form a previously registered roadmap node to a currently registered roadmap node means that the robotic cleaning device is driving without colliding or detecting an obstacle in between the previously registered roadmap node and the currently registered roadmap node.


In case an obstacle is detected in between two roadmap nodes the robotic cleaning device will navigate around it and continue to register roadmap nodes while doing that.


According to a preferred embodiment the method may comprise the step of adding a shortcut link between a previously registered roadmap node of a first sequence, and a currently registered roadmap node of a second sequence of registered roadmap nodes, if the two roadmap nodes are found to be close enough so that it can be safely assumed that the robotic cleaning device can drive in between them without risking any collision.


The safe assumption may for example be considered, if no obstacle is detected in between the previously registered roadmap node of the first sequence and the currently registered roadmap node of the second sequence, said second sequence being arranged at an offset from the first sequence.


The shortcut links increase the robustness of the navigation. The robotic cleaning device is capable of driving and navigating between sequence sections by using the shortcut links. The shortcut links may shorten transportation paths quite substantially, as disclosed later herein.


The criterion for adding a shortcut in between the previously registered roadmap node of the first sequence and the currently registered roadmap node of the second sequence may be that the offset is smaller than a width of the robotic cleaning device.


Generally the offset may be chosen to be less than one of the dimensions of the robotic cleaning device, for example the width or length of the robotic cleaning device.


This may help the robotic cleaning device to ensure that there is no obstacle in between the registered roadmap node of the first sequence section and the currently registered roadmap node of the second sequence section.


The first sequence section and the second sequence section may each comprise at least two roadmap nodes linked by a roadmap link.


In an embodiment the method may further comprise the step of determining a shortest distance between a first position, preferably within the roadmap graph, and a second position, preferably within the roadmap graph, by identifying the registered roadmap node in proximity to the first position and the registered roadmap node in proximity to the second position and then calculating a transportation sequence, which comprises the smallest amount of linked registered roadmap nodes that lead from the first position to the second position.


Alternatively to the above the robotic cleaning device may be configured to measure the geometrical length of each link, thus roadmap link and shortcut link, and choose a path or sequence that has the shortest total distance, said total distance being the sum of the geometrical lengths of all links involved in the path or sequence. This may provide even shorter sequences.


The transportation sequence may comprise roadmap links and shortcut links.


The smallest amount of linked roadmap nodes points generally to the shortest distance from the first position to the second position. The transportation sequence uses the roadmap links and shortcut links that are established and thus avoids a collision with an obstacle.


In an embodiment the intervals may be time intervals.


The time intervals may be in the range of 1 to 30 seconds, preferably 3 to 20 seconds and more preferably from 5 to 15 seconds.


The robotic cleaning device may be configured to only register roadmap nodes while moving on the surface to be cleaned.


In another embodiment the intervals, between registered roadmap nodes, may be distance intervals.


The distance intervals may be in the range of 1 to 20 cm, preferably 5 to 15 cm and more preferably in the range of 7 to 13 cm.


Alternatively the distance intervals may be in the range of 1% to 100% of the largest dimension of the robotic cleaning device, more preferably 20% to 50% of the largest dimension of the robotic cleaning device.


The distance intervals may be measured by a location-sensor connected to a processing unit.


Advantageously the intervals may be shortened if it is detected that the robotic cleaning device is changing its direction of movement more than a predefined upper threshold value.


This may increase accuracy when the robotic cleaning device is navigating in complex areas, said areas having for example many obstacles or a complicated layout.


The upper threshold value may for example be measured as amount of direction changes of the robotic cleaning device per time or amount of direction changes of the robotic cleaning device per distance.


In another embodiment the intervals may be extended if it is detected that the robotic cleaning device is changing its direction of movement less than a predefined lower threshold value.


This may reduce the amount of roadmap nodes and thus data that is produced.


The lower threshold value may for example also be measured as amount of direction changes of the robotic cleaning device per time or amount of direction changes of the robotic cleaning device per distance.


In another embodiment the method may further comprise a step of adding straight shortcut links between straightly linked roadmap nodes by connecting a first roadmap node and a last roadmap node of a straight sequence segment.


The straight shortcut links may simplify the roadmap graph.


It may be advantageous not to delete the originally registered roadmap nodes arranged in between the first roadmap node and the last roadmap node of the straightly linked roadmap nodes since the roadmap nodes arranged in between may be needed for the shortcut links between a first sequence section and a second sequence section.


The straight shortcut links may be advantageous when the robotic cleaning device navigates through long narrow corridors or the like.


In another embodiment the roadmap nodes may comprise additional information about the status of the robotic cleaning device at the time of registering the roadmap node and/or the roadmap link.


The additional information may be used to select, among multiple possible roadmap nodes, an arbitrary sequence of roadmap nodes that reduces the risk for collision with an obstacle.


The additional information may for example comprise tags such as “carpet edge”, “wall”, “door sill” if such objects or obstacles are encountered, in order to improve the safety of the navigation.


Herein is also disclosed a robotic cleaning device comprising a main body, a propulsion system arranged to move the robotic cleaning device, a contact detecting portion connected to the main body and arranged to detect if the robotic cleaning device is in contact with an object and a dead reckoning sensor operatively connected to the propulsion system. The robotic cleaning device may further comprise a processing unit arranged to control the propulsion system, whereby the processing unit may be connected to the dead reckoning sensor and configured to perform the method comprising any of the previously described steps and/or features.


Disclosed herein is further a computer program comprising computer-executable instructions for causing a robotic cleaning device to perform the method comprising any of the previously described steps and/or features, when the computer-executable instructions are executed on a processing unit included in the robotic cleaning device.


Disclosed is further a computer program product comprising a computer readable storage medium, the computer readable storage medium having the computer program according to the above embodied therein.


Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to “a/an/the element, apparatus, component, means, device, step, etc.” are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, device, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.





BRIEF DESCRIPTION OF THE DRAWINGS

The invention is now described, by way of example, with reference to the accompanying drawings, in which:



FIG. 1 schematically illustrates a top down view onto an embodiment of a robotic cleaning device according to the invention;



FIG. 2 schematically illustrates a front view onto a robotic cleaning device according to an embodiment of the invention;



FIG. 3 schematically illustrates the steps of registering roadmap nodes and forming roadmap links according to a method of the invention;



FIG. 4 schematically illustrates the step of adding shortcuts in between roadmap nodes;



FIG. 5 schematically illustrates the step of adding straight shortcuts in between straightly connected roadmap nodes;



FIG. 6 schematically illustrates a roadmap graph of cleaning environment after the completion of a cleaning by the robotic cleaning device;



FIG. 7 schematically illustrates the step of determining and calculating a shortest distance between a first position and a second position in the roadmap graph of FIG. 6; and



FIG. 8 schematically illustrates the steps of the method according to the invention.





DETAILED DESCRIPTION

The invention will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the invention are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout the description.


The invention relates to robotic cleaning devices, or in other words, to automatic, self-propelled machines for cleaning a surface, e.g. a robotic vacuum cleaner, a robotic sweeper or a robotic floor washer. The robotic cleaning device 10 according to the invention can be mains-operated and have a cord, be battery-operated or use any other kind of suitable energy source, for example solar energy.



FIG. 1 shows a robotic cleaning device 10 according to an embodiment of the present invention in a bottom view, i.e. the bottom side of the robotic cleaning device 10 is shown. The arrow indicates the forward direction of the robotic cleaning device. The robotic cleaning device 10 comprises a main body 11 housing components such as a propulsion system comprising driving means in the form of two electric wheel motors 15a, 15b for enabling movement of the driving wheels 12, 13, such that the robotic cleaning device 10 can be moved over a surface to be cleaned. Each wheel motor 15a, 15b is capable of controlling the respective driving wheel 12, 13 to rotate independently of each other in order to move the robotic cleaning device 10 across a surface to be cleaned. A number of different driving wheel arrangements, as well as various wheel motor arrangements, may be envisaged. It should be noted that the robotic cleaning device 10 may have any appropriate shape, such circular-shaped main body 11 as illustrated, or a triangular-shaped main body.


As an alternative to the above described propulsion system, a track propulsion system may be used or even a hovercraft propulsion system.


The propulsion system is further connected to two dead reckoning sensors 30, 30′, one assigned to each driving wheel 12, 13, as illustrated in FIG. 1. The dead reckoning sensors 30, 30′ are configured to independently measure distances traveled by the robotic cleaning device 10 by observing the movement and turns, respectively, of the driving wheels 12, 13, in order to help to position the robotic cleaning device 10, for example within a room.


The embodiment of the robotic cleaning device 10 as illustrated in FIG. 1 comprises two dead reckoning sensors 30, 30′, it is however possible to envisage robotic cleaning devices comprising only one dead reckoning sensor 30, 30′.


A controller such as processing unit 16 controls the wheel motors 15a, 15b to rotate the driving wheels 12, 13 as required in view of information received from an obstacle detecting device (shown in FIG. 2) for detecting obstacles in the form of walls, floor lamps, table legs, around which the robotic cleaning device must navigate. The dead reckoning sensors 30, 30′ are connected to the processing unit 16, for example via the electric wheel motors 15a, 15b, as illustrated in FIG. 1.


The obstacle detecting device may be embodied in the form of infrared (IR) sensors and/or sonar sensors, a microwave radar, a 3D sensor system registering its surroundings, implemented by means of e.g. a 3D camera, a camera in combination with lasers, a laser scanner, etc. for detecting obstacles and communicating information about any detected obstacle to the processing unit 16. The processing unit 16 communicates with the wheel motors 15a, 15b to control movement of the wheels 12, 13 in accordance with information provided by the obstacle detecting device.


In FIG. 1 the width W of the robotic cleaning device 10 is further illustrated. As the main body 11 has a round shape, the width W corresponds to a diameter of the main body. In general terms the width W may be defined as the widest part or largest dimension of the robotic cleaning device 10 as measured in a forward direction M.


The main body 11 may optionally be provided with a cleaning member 17 for removing debris and dust from the surface to be cleaned in the form of a rotatable brush roll arranged in an opening 18 at the bottom of the robotic cleaner 10. Thus, the rotatable brush roll 17 is arranged along a horizontal axis in the opening 18 to enhance the dust and debris collecting properties of the cleaning device 10. In order to rotate the brush roll 17, a brush roll motor 19 is operatively coupled to the brush roll to control its rotation in line with instructions received from the processing unit 16.


Moreover, the main body 11 of the robotic cleaner 10 comprises a suction fan 20 creating an air flow for transporting debris to a dust bag or cyclone arrangement (not shown) housed in the main body via the opening 18 in the bottom side of the main body 11. The suction fan 20 is driven by a fan motor 21 connected to the processing unit 16 from which the fan motor 21 receives instructions for controlling the suction fan 20. It should be noted that a robotic cleaning device 10 having either one of the rotatable brush roll 17 and the suction fan 20 for transporting debris to the dust bag may be envisaged. A combination of the two will however enhance the debris-removing capabilities of the robotic cleaning device 10.


Alternatively, the robotic cleaning device 10 may comprise a mop (not shown) and/or a rotating floor brush (not shown).


With further reference to FIG. 1, the processing unit 16 may be embodied in the form of one or more microprocessors arranged to execute a computer program 25 downloaded to a suitable storage medium 26 associated with the microprocessor, such as a Random Access Memory (RAM), a Flash memory or a hard disk drive. The processing unit 16 is arranged to carry out a method according to embodiments of the present invention when the appropriate computer program 25 comprising computer-executable instructions is downloaded to the storage medium 26 and executed by the processing unit 16. The storage medium 26 may also be a computer program product comprising the computer program 25. Alternatively, the computer program 25 may be transferred to the storage medium 26 by means of a suitable computer program product, such as a digital versatile disc (DVD), compact disc (CD) or a memory stick. As a further alternative, the computer program 25 may be downloaded to the storage medium 26 over a network. The processing unit 16 may alternatively be embodied in the form of a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), etc.


In FIG. 1 is further a contact detecting portion 32 illustrated. The contact detecting portion 32 is arranged at a front end of the robotic cleaning device 10 as seen in a direction of movement. The contact detecting portion 32 may extend over the whole front part of the robotic cleaning device 10, similar to a park distance sensor of a modern car. Alternatively, the contact detecting portion 32 may only extend over the front extremity of the robotic cleaning device 10, as illustrated in FIG. 1. The contact detecting portion 32 is arranged in order to detect whether or not the robotic cleaning device 10 is in contact with an object or landmark. This may be useful when a collision with obstacles has to be avoided.



FIG. 2 shows a front view of the robotic cleaning device 10 according to an embodiment illustrating the previously mentioned obstacle detecting device in the form of a 3D camera system 22 comprising at least a camera 23 and a first and a second structured light source 27, 28, which may be horizontally or vertically oriented line lasers. Further illustrated is the processing unit 16, the main body 11, the driving wheels 12, 13, and the rotatable brush roll 17 previously discussed with reference to FIG. 1. The processing unit 16 is operatively coupled to the camera 23 for recording images of a vicinity of the robotic cleaning device 10. The first and second structured light sources 27, 28 may preferably be vertical line lasers and are arranged lateral of the camera 23 configured to illuminate a height and a width that is greater than the height and width of the robotic cleaning device 10. The camera 23 is controlled by the processing unit 16 to capture and record a plurality of images per second. Data from the images is extracted by the processing unit 16 and the data is typically saved in the storage medium 26 along with the computer program 25.


The first and second structured light sources 27, 28 are configured to scan, preferably in a vertical orientation, the vicinity of the robotic cleaning device 10, normally in the direction of movement of the robotic cleaning device 10. The first and second structured light sources 27, 28 are configured to send out laser beams, which illuminate furniture, walls and other obstacles of a home or room. The camera 23 is controlled by the processing unit 16 to capture and record images from which the processing unit 16 creates a representation or layout of the surroundings that the robotic cleaning device 10 is operating in, by extracting features from the images and by measuring the distance covered by the robotic cleaning device 10, while the robotic cleaning device 10 is moving across the surface to be cleaned. Thus, the processing unit 16 may derive positional data of the robotic cleaning device 10 with respect to the surface to be cleaned from the recorded images, to generate a 3D representation of the surroundings in particular the obstacles.


The 3D representation generated from the images recorded by the 3D camera system 22 thus facilitates detection of obstacles in the form of walls, floor lamps, table legs, etc. around which the robotic cleaning device 10 must navigate as well as rugs, carpets, doorsteps, etc., that the robotic cleaning device 10 must traverse.


With respect to FIG. 2, for illustrational purposes, the 3D camera system 22 is separated from the main body 11 of the robotic cleaning device 10. However, in a practical implementation, the 3D camera system 22 is likely to be integrated with the main body 11 of the robotic cleaning device 10 to minimize the height of the robotic cleaning device 10, thereby allowing it to pass under obstacles, such as e.g. a sofa.


The robotic cleaning device 10 has now been described comprising an obstacle detecting device having a 3D camera 23 and first and second structured light sources 27, 28, as this provides for an efficient and rather quick navigation of the robotic cleaning device. However, in its simplest form the robotic cleaning device 10 may only comprise the contact detecting portion 32, since this contact detecting portion 32 enables the robotic cleaning device 10 to navigate around detected obstacles. For the method as illustrated herein, it is sufficient that the robotic cleaning device 10 comprises the contact detecting portion 32, the obstacle detecting device is not essential to perform the method described herein.



FIGS. 3 to 5 illustrate steps of the method according to the present invention. In the following the terms roadmap node 34, roadmap link 36 and roadmap graph 38 (c.f. FIGS. 6 and 7) relate to the following:


Roadmap node 34: a position of the robotic cleaning device 10 at a specific point in time whereby the roadmap node is a virtual point, for example stored on the storage medium 26, said virtual point eventually building a roadmap graph;


Roadmap link 36: a record, which also may be stored on the storage medium 26, that connects two or more roadmap nodes 34, 34′, 34″ in between which the robotic cleaning device could drive directly without colliding with any obstacles;


Roadmap graph 38: a virtual map, for example stored on the storage medium 26, of the surface to be cleaned comprising at least some of the roadmap nodes 34 and the roadmap links 36.


The roadmap graph 38 may comprise additional features as will be described later herein.



FIG. 3 illustrates how the robotic cleaning device 10 moves in a direction M while registering S01 roadmap nodes 34, 34′ at intervals. When it is detected that the robotic cleaning device 10 could directly drive or move from a previously registered roadmap node 34′ to a currently registered roadmap node 34 the two roadmap nodes 34′, 34 are linked S02 by a roadmap link 36. As illustrated in FIG. 3, the robotic cleaning device 10 has been driving straight for a sequence of five roadmap nodes 34, 34′ without colliding with any obstacle and thus these roadmap nodes 34′, 34 are all linked together by roadmap links 36. This indicates to the robotic cleaning device 10 that it is safe to drive along these roadmap links 36 and that his may be done again if necessary for example for transportation (c.f. FIG. 7).


The linked roadmap nodes 34, 34′ may form a sequence 54. This sequence 54 is continuously extended as the robotic cleaning device 10 is driving and cleaning, as for example illustrated in FIGS. 6 and 7. It should however be noted that the sequence 54 does not have to be continuous it may be interrupted.


The intervals between the registered roadmap nodes 34, 34′ may be time intervals or distance intervals. Thus the roadmap nodes 34, 34′ may be dropped or registered at time intervals of for example 1 to 30 seconds, preferably 3 to 20 seconds and more preferably from 5 to 15 seconds or at distance intervals of for example 1 to 20 cm, preferably 5 to 15 cm and more preferably in the range of 7 to 13 cm.


Alternatively the distance intervals may be in the range of 1% to 100% of the largest dimension of the robotic cleaning device 10, more preferably 20% to 50% of the largest dimension of the robotic cleaning device 10, which is in the illustrated case the diameter or width W but may in other cases be a length or width of the robotic cleaning device.



FIG. 4 illustrates additionally to the steps illustrated together with FIG. 3, how the robotic cleaning device 10 is adding S03 a shortcut link 40 between a registered roadmap node 34″ of a first sequence section 42 or first sequence of a sequence 54 of registered roadmap nodes and a currently registered roadmap node 34 of a second sequence section 44 or second sequence of the sequence 54 of registered roadmap nodes, if no obstacle is detected in between the registered roadmap node of the first sequence section 42 and the currently registered roadmap node 34 of the second sequence section 44. As shown in FIG. 4, the second sequence section 44 is arranged at an offset D from the first sequence section 42.


The first sequence section 42 is illustrated as a dashed line in FIG. 4 for illustrative purposes in order to easier distinguish between the two sequence sections 42, 44. Additionally, the robotic cleaning device 10 is illustrated in a dashed shape to show that it drove along the second sequence section 44 while adding the illustrated shortcut links 40. The robotic cleaning device is further shown transparent in order to illustrate the registering S01 of the current roadmap node 34.


The robotic cleaning device 10 is thus configured to follow previously registered roadmap nodes 34″ as soon as the processing unit 16 detects that previously registered roadmap nodes 34″ are encountered, which is usually the case as for example illustrated in FIGS. 6 and 7. In other words, the robotic cleaning device 10 is capable of noticing where it has been before, since it will detect and thus recognize these areas because of the previously registered roadmap nodes 34′, 34″.


The shortcut links 40 thus connect the at least approximately parallel first sequence section 42 and second sequence section 44 if no obstacle is detected. Shortcut links 40 may be added continuously whenever possible or only sequentially at defined distance or time intervals.


The offset D between the second sequence section 44 and the first sequence section 42 must be smaller than the width W (c.f. FIG. 1) of the robotic cleaning device 10, only then is safe to assume that no obstacle is arranged in between the currently registered roadmap node 34 of the second sequence section 44 and the previously registered roadmap node 34″ of the first sequence section 42. The offset D may further be chosen to be less than a width (not illustrated in the figures) of the opening 18 of the suction fan 20. The processing unit 16 may be configured to navigate the robotic cleaning device 10 accordingly at an offset D less than the width W of the robotic cleaning device 10, when previously registered roadmap nodes 34″ are encountered.



FIG. 5 illustrates how straight shortcut links 46, 46′, 46″ may be added S04 between straightly linked roadmap nodes 34′″, 34a, 34b forming a straight sequence section 43. When the processing unit 16 detects that the robotic cleaning device 10 was driving at least approximately straight for sequence of roadmap nodes 34a, 34′″, 34b it may add S04 straight shortcut links 46, 46′, 46″ between a first roadmap node 34a and a last roadmap node 34b of a straight sequence of roadmap nodes 34a, 34b, 34′″. In order to add shortcut links 40 (c.f. FIG. 4) later on, thus when following (not shown in the figures) the sequence of roadmap nodes 34′″, 34a, 34b illustrated in FIG. 5 upon encountering them, the roadmap nodes 34′″ in between the first roadmap node 34a and the last roadmap node 34b are not deleted. The robotic cleaning device 10 may thus revert back to those intermediate roadmap nodes 34′″ in case a shortcut link 36 needs to be added later on to a roadmap node 34 of another sequence section 42, 44, as shown and described referring to FIG. 4.


In case the robotic cleaning device 10 detects (not shown in the figures) an obstacle in between a currently registered roadmap node of the second sequence section and the previously registered roadmap node 34″ of the first sequence section, the robotic cleaning 10 will navigate around it using the contact detecting portion 32 and optionally the obstacle detecting device, while registering S01 and linking S02 roadmap nodes until previously registered roadmap nodes 34″ suitable for adding S03 shortcut links 40 are again encountered.


For the sake of simplicity the robotic cleaning device 10 is not shown in FIG. 5. However its current position would be at the current registered roadmap node 34.


Further, it should be mentioned that the roadmap graph 38′ as schematically illustrated in FIG. 5 may for instance be established while the robotic cleaning device 10 was following a wall or the like.


Referring now to FIG. 6, which illustrates a roadmap graph 38 of a surface to be cleaned after completion of the cleaning and thus after the roadmap nodes 34 have been registered. The roadmap nodes 34, 34′, 34″, 34″″, 34′″″, 34a, 34b, the roadmap links 36 and the shortcut links 40 are illustrated, said roadmap nodes 34, 34′, 34″, 34″″, 34′″″, 34a, 34b, the roadmap links 36 and the shortcut links 40 forming a complete and robust roadmap graph 38. The roadmap graph 38 comprises the positional information about two obstacles 48, 50 thus teaching the robotic cleaning device 10 that it cannot drive in these areas. The starting point S of the cleaning and registering of roadmap nodes 34 and the current position C of the robotic cleaning device 10 are also visible in FIG. 6. FIG. 6 illustrates well how the robotic cleaning device 10 and the processing unit 16, respectively, add shortcut links 40 whenever previously registered roadmap nodes 34″ of a an earlier sequence section 42 are encountered.


For illustrated purposes potential straight shortcuts 46, 46′, 46″ as shown in FIG. 5, are not shown in FIG. 6 although they may be present.



FIG. 7 illustrates schematically how the roadmap graph 38 of FIG. 6 may be used to determine S05 a shortest distance from a first position A to a second position B. The shortest distance from positions A to B may be determined by identifying a registered roadmap node 34″″ close to the first position A and another registered roadmap node close 34′″″ close to the second position and by then calculating a transportation sequence 52. The transportation sequence 52 may be chosen as the sequence comprising the smallest amount of linked registered roadmap nodes 34, 34″″, 34′″″ that lead from the first position A to the second position B. Linked registered roadmap nodes 34, 34″″, 34′″″ is herewith to be understood as registered roadmap nodes 34, 34″″, 34′″″ being linked by roadmap links 36, shortcut links 40 and/or straight shortcut links 46 (not shown in FIG. 7).


Determining S05 a shortest distance between a first position A and a second position B by identifying a registered roadmap node 34″″ in proximity to the first position A and another registered roadmap node 34′″″ in proximity to the second position B and then calculating a transportation sequence 52 may alternatively involve the calculation of a transportation sequence (not shown), which comprises the shortest total distance, when summarizing the geometrical length of all roadmap links 36 and shortcut links 40 involved in the transportation sequence. In some cases, for example when many roadmap nodes are involved, this may lead to a shorter transportation sequence 52 than the calculation of the smallest amount of linked roadmap nodes 34, 34″″, 34′″″ that lead from the first position A to the second position B.



FIGS. 6 and 7 further illustrate another sequence 54′ of roadmap nodes 34, 34′, 34″″, 34′″″ linked by roadmap links 36. This sequence 54′ is illustrated as being continuous this is however not necessarily the case, as previously mentioned.


The sequence 54′ further comprises a plurality of sequence sections 42, 43, 44 as previously described.


The robotic cleaning device 10 is thus capable to navigate safely and with a small risk of getting lost. Additionally, even if a new obstacle is added to the cleaning environment in between a first cleaning session of a room or surface and a second cleaning session of the same room or surface, the robotic cleaning device 10 will be able to navigate safely since the registered roadmap nodes 34a, 34b, 34′, 34″, 34′″, 34″″, 34′″″, the roadmap links 36, the shortcut links 40 and the straight shortcut links 46, 46′, 46″ are deleted after each completed cleaning session. The roadmap graph 38 is thus always up to date and experience based leaving the robotic cleaning device 10 with a reliable and robust method for navigation.


The roadmap nodes 34a, 34b, 34′, 34″, 34′″, 34″″, 34′″″ may comprise positional information and additional information about the status of the robotic cleaning device 10 at the time of registering the roadmap node 34a, 34b, 34′, 34″, 34′″, 34″″, 34′″″ and/or the roadmap link 36. The additional information may for example be used to determine an arbitrary sequence of roadmap nodes that reduce the risk for collision with an obstacle.


In other words if the robotic cleaning device 10 for example detects that is regularly cross an edge of a carpet, the processing unit 16 may be configured to plan the cleaning and in particular a potential transportation sequence 52 accordingly to avoid that the carpet edge needs to be crossed if possible. Thus the registered roadmap nodes 34a, 34b, 34′, 34″, 34′″, 34″″, 34′″″ may provide the robotic cleaning device 10 and the processing unit 16, respectively, with additional information about the surface to be cleaned.


Further the additional information may comprise a tag such as “bumpy” which means that a certain area of the surface was bumpy or difficult to drive on, which will teach the robotic cleaning device 10 and the processing unit 16, respectively, to avoid this area when planning a sequence in order to make this sequence safer and more robust.


The time or distance intervals as previously described may not be regular or continuous they may vary depending on the amount of direction changes of the robotic cleaning device 10 during a specific time period. These direction changes may be easily detected by the dead reckoning sensor 30, 30′.



FIG. 8 illustrates the steps according to the present invention. If an obstacle is detected (not shown), for instance when trying to add shortcut links 40, the robotic cleaning device 10 will not add a shortcut link 40 and go back to the first step and registering S01 and linking S02 roadmap nodes 34 while following the edge of the obstacle until previously registered roadmap nodes of a previous sequence section are again encountered.


The invention has mainly been described above with reference to a few embodiments. However, as is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the invention, as defined by the appended patent claims.

Claims
  • 1. A method of operating a robotic cleaning device over a surface to be cleaned, the method comprising: autonomously driving over the surface and cleaning the surface, by the robotic cleaning device;during the autonomous driving, autonomously registering, by the robotic cleaning device, a plurality of roadmap nodes at intervals on the surface, each of the plurality of roadmap nodes comprising respective positional information;in response to autonomously driving directly from a previously registered roadmap node of the plurality of roadmap nodes to a currently registered roadmap node of the plurality of roadmap nodes, autonomously generating a roadmap link between the previously registered roadmap node and the currently registered roadmap node;compiling the plurality of roadmap nodes and a plurality of roadmap links into a roadmap graph; andusing the roadmap graph to navigate the robotic cleaning device during a subsequent cleaning.
  • 2. The method according to claim 1, further comprising adding a shortcut link between a registered roadmap node of a first sequence section of registered roadmap nodes and a currently registered roadmap node of a second sequence section of registered roadmap nodes, if no obstacle is detected in between the registered roadmap node of the first sequence section and the currently registered roadmap node of the second sequence section, the second sequence section being arranged at an offset from the first sequence section.
  • 3. The method according to claim 2, wherein the offset is smaller than a dimensional size of the robotic cleaning device, the dimensional size being a length or a width of the robotic cleaning device.
  • 4. The method according to claim 2, wherein the first sequence section and the second sequence section each comprises at least two roadmap nodes linked by a respective roadmap link.
  • 5. The method according to claim 1, further comprising determining a shortest distance between a first position and a second position by identifying a first registered roadmap node in proximity to the first position and a second registered roadmap node in proximity to the second position and calculating a transportation sequence comprising a smallest number of linked registered roadmap nodes that lead from the first position to the second position.
  • 6. The method according to claim 1, further comprising determining a shortest distance between a first position and a second position by identifying a first registered roadmap node in proximity to the first position and a second registered roadmap node in proximity to the second position and calculating a transportation sequence comprising a shortest total distance from the first position to the second position, as measured by the sum of the geometrical length of all roadmap links and shortcut links involved in the transportation sequence.
  • 7. The method according to claim 1, wherein the intervals comprise time intervals.
  • 8. The method according to claim 1, wherein the intervals comprise distance intervals.
  • 9. The method according to claim 1, further comprising increasing a frequency of the intervals when the robotic cleaning device changes its direction of movement more frequently than a predefined upper threshold frequency value.
  • 10. The method according to claim 1, further comprising reducing a frequency of the intervals when the robotic cleaning device changes its direction of movement less frequently than a predefined lower threshold frequency value.
  • 11. The method according to claim 1, further comprising adding straight shortcut links between a plurality of linked roadmap nodes forming a straight sequence segment by connecting a first one of the plurality of linked roadmap nodes and a last one of the plurality of roadmap nodes.
  • 12. The method according to claim 1, wherein the roadmap nodes comprise additional information about the status of the robotic cleaning device at the time of registering the roadmap node.
  • 13. The method according to claim 11, wherein the additional information is used to select among multiple possible sequences of roadmap nodes between the registering or roadmap nodes, an arbitrary sequence of roadmap nodes that reduce the risk for collision with an obstacle.
  • 14. A robotic cleaning device comprising: a main body;a propulsion system arranged to move the robotic cleaning device;a contact detecting portion connected to the main body and arranged to detect if the robotic cleaning device is in contact with an object;a dead reckoning sensor operatively connected to the propulsion system;a processing unit arranged to control the propulsion system;wherein the processing unit is connected to the dead reckoning sensor and configured to: autonomously drive the robotic cleaning device over a surface and clean the surface;during the autonomous driving, autonomously register a plurality of roadmap nodes at intervals on the surface during cleaning, each of the plurality of roadmap nodes comprising respective positional information;in response to autonomously driving directly from a previously registered roadmap node of the plurality of roadmap nodes to a currently registered roadmap node of the plurality of roadmap nodes, autonomously generate a roadmap link between the previously registered roadmap node and the currently registered roadmap node;compile the plurality of roadmap nodes and a plurality of roadmap links into a roadmap graph; anduse the roadmap graph to navigate the robotic cleaning device during a subsequent cleaning.
  • 15. A computer program comprising computer-executable instructions stored in a non-transitory medium for causing a robotic cleaning device to: autonomously drive the robotic cleaning device over a surface and clean the surface;during the autonomous driving, autonomously register a plurality of roadmap nodes at intervals on a surface as the robotic cleaning device traverses the surface, each of the plurality of roadmap nodes comprising respective positional information;in response to autonomously driving directly from a previously registered roadmap node of the plurality of roadmap nodes to a currently registered roadmap node of the plurality of roadmap nodes, autonomously generate a roadmap link between the previously registered roadmap node and the currently registered roadmap node;compile the plurality of roadmap nodes and a plurality of roadmap links into a roadmap graph; anduse the roadmap graph to navigate the robotic cleaning device during a subsequent cleaning.
  • 16. The computer program of claim 15, wherein the computer executable instructions are executed on a processing unit in the robotic cleaning device.
PCT Information
Filing Document Filing Date Country Kind
PCT/EP2014/077947 12/16/2014 WO 00
Publishing Document Publishing Date Country Kind
WO2016/095965 6/23/2016 WO A
US Referenced Citations (986)
Number Name Date Kind
1286321 Hoover Dec 1918 A
1401007 Staples Dec 1921 A
3010129 Moore Nov 1961 A
3233274 Kroll Feb 1966 A
3550714 Bellinger Dec 1970 A
3570227 Bellinger Mar 1971 A
3713505 Muller Jan 1973 A
3837028 Bridge Sep 1974 A
4028765 Liebscher Jun 1977 A
4036147 Westling Jul 1977 A
4114711 Wilkins Sep 1978 A
4119900 Kremnitz Oct 1978 A
4306174 Mourier Dec 1981 A
4306329 Yokoi Dec 1981 A
4369543 Chen Jan 1983 A
4502173 Patzold Mar 1985 A
4627511 Yajima Dec 1986 A
4647209 Neukomm Mar 1987 A
4800978 Wasa Jan 1989 A
4822450 Davis Apr 1989 A
4825091 Breyer Apr 1989 A
4836905 Davis Jun 1989 A
4838990 Jucha Jun 1989 A
4842686 Davis Jun 1989 A
4849067 Jucha Jul 1989 A
4854000 Takimoto Aug 1989 A
4864511 Moy Sep 1989 A
4872938 Davis Oct 1989 A
4878003 Knepper Oct 1989 A
4886570 Davis Dec 1989 A
4918607 Wible Apr 1990 A
4919224 Shyu Apr 1990 A
4922559 Wall May 1990 A
4959192 Trundle Sep 1990 A
4962453 Pong Oct 1990 A
4989818 Trundle Feb 1991 A
5001635 Yasutomi Mar 1991 A
5006302 Trundle Apr 1991 A
5023444 Ohman Jun 1991 A
5032775 Mizuno Jul 1991 A
5034673 Shoji Jul 1991 A
5042861 Trundle Aug 1991 A
5045118 Mason Sep 1991 A
5086535 Grossmeyer Feb 1992 A
5095577 Jonas Mar 1992 A
5107946 Kamimura Apr 1992 A
5155683 Rahim Oct 1992 A
5243732 Koharagi Sep 1993 A
5245177 Schiller Sep 1993 A
5276933 Hennessey Jan 1994 A
5279672 Betker Jan 1994 A
5293955 Lee Mar 1994 A
5307273 Oh Apr 1994 A
5309592 Hiratsuka May 1994 A
5341540 Soupert Aug 1994 A
5345639 Tanoue Sep 1994 A
5349378 FereydounMaali Sep 1994 A
5353224 Lee Oct 1994 A
5367458 Roberts et al. Nov 1994 A
5369347 Yoo Nov 1994 A
5377106 Drunk Dec 1994 A
5390627 van der Berg Feb 1995 A
5398632 Goldbach Mar 1995 A
5402051 Fujiwara Mar 1995 A
5440216 Kim Aug 1995 A
5444965 Colens Aug 1995 A
5446356 Kim Aug 1995 A
5454129 Kell Oct 1995 A
5518552 Tanoue May 1996 A
5534762 Kim Jul 1996 A
5548511 Bancroft Aug 1996 A
5560077 Crotchett Oct 1996 A
5568589 Hwang Oct 1996 A
5621291 Lee Apr 1997 A
5646494 Han Jul 1997 A
5666689 Andersen Sep 1997 A
5682313 Edlund Oct 1997 A
5682640 Han Nov 1997 A
5687294 Jeong Nov 1997 A
5698957 Sowada Dec 1997 A
5745946 Thrasher May 1998 A
5758298 Guldner May 1998 A
5778554 Jones Jul 1998 A
5781960 Kilstrom Jul 1998 A
5787545 Colens Aug 1998 A
5815880 Nakanishi Oct 1998 A
5825981 Matsuda Oct 1998 A
5841259 Kim Nov 1998 A
5852984 Matsuyama Dec 1998 A
5867800 Leif Feb 1999 A
5890250 Lange Apr 1999 A
5896488 Jeong Apr 1999 A
5903124 YuichiKawakami May 1999 A
5926909 McGee Jul 1999 A
5933902 Frey Aug 1999 A
5935179 Kleiner Aug 1999 A
5940927 Haegermarck Aug 1999 A
5942869 Katou Aug 1999 A
5947051 Geiger Sep 1999 A
5959423 Nakanishi Sep 1999 A
5959424 Elkmann Sep 1999 A
5966765 Hamada Oct 1999 A
RE36391 vandenBerg Nov 1999 E
5983833 van der Lely Nov 1999 A
5987696 Wang Nov 1999 A
5991951 Kubo Nov 1999 A
5995884 Allen Nov 1999 A
5997670 Walter Dec 1999 A
5999865 Bloomquist et al. Dec 1999 A
6012470 Jones Jan 2000 A
6024107 Jones Feb 2000 A
6064926 Sarangapani May 2000 A
6076662 Bahten Jun 2000 A
6082377 Frey Jul 2000 A
6124694 Bancroft Sep 2000 A
6142252 Kinto Nov 2000 A
6176067 Bahten Jan 2001 B1
6213136 Jones Apr 2001 B1
6226830 Hendriks May 2001 B1
6230360 Singleton May 2001 B1
6240342 Fiegert et al. May 2001 B1
6251551 Kunze-Concewitz Jun 2001 B1
6255793 Peless Jul 2001 B1
6263989 Won Jul 2001 B1
6300737 Bergvall Oct 2001 B1
6311366 Sepke Nov 2001 B1
6327741 Reed Dec 2001 B1
6339735 Peless Jan 2002 B1
6358325 Andreas Mar 2002 B1
6360801 Walter Mar 2002 B1
6370452 Pfister Apr 2002 B1
6370453 Sommer Apr 2002 B2
6381801 Clemons, Sr. May 2002 B1
6389329 Colens May 2002 B1
6413149 Wada Jul 2002 B1
6417641 Peless Jul 2002 B2
6431296 Won Aug 2002 B1
6438456 Feddema Aug 2002 B1
6443509 Levin Sep 2002 B1
6457199 Frost Oct 2002 B1
6457206 Judson Oct 2002 B1
6459955 Bartsch Oct 2002 B1
6465982 Bergvall Oct 2002 B1
6481515 Kirkpatrick Nov 2002 B1
6482678 Frost Nov 2002 B1
6493612 Bisset Dec 2002 B1
6493613 Peless Dec 2002 B2
6496754 Song Dec 2002 B2
6504610 Bauer Jan 2003 B1
6519804 Vujik Feb 2003 B1
6525509 Petersson Feb 2003 B1
D471243 Cioffi Mar 2003 S
6532404 Colens Mar 2003 B2
6535793 Allard Mar 2003 B2
6571415 Gerber Jun 2003 B2
6580246 Jacobs Jun 2003 B2
6581239 Dyson Jun 2003 B1
6594844 Jones Jul 2003 B2
6597143 Song Jul 2003 B2
6601265 Burlington Aug 2003 B1
6605156 Clark Aug 2003 B1
6609962 Wakabayashi Aug 2003 B1
6611120 Song Aug 2003 B2
6611318 LaPolice Aug 2003 B2
6615108 Peless Sep 2003 B1
6615885 Ohm Sep 2003 B1
6633150 Wallach Oct 2003 B1
6637446 Frost Oct 2003 B2
6658325 Zweig Dec 2003 B2
6661239 Ozick Dec 2003 B1
6662889 De Fazio Dec 2003 B2
6667592 Jacobs Dec 2003 B2
6668951 Won Dec 2003 B2
6671592 Bisset Dec 2003 B1
6690134 Jones Feb 2004 B1
6726823 Wang Apr 2004 B1
6732826 Song May 2004 B2
6745431 Dijksman Jun 2004 B2
6748297 Song Jun 2004 B2
6769004 Barrett Jul 2004 B2
6774596 Bisset Aug 2004 B1
6775871 Finch Aug 2004 B1
6781338 Jones Aug 2004 B2
6809490 Jones Oct 2004 B2
6810305 Kirkpatrick, Jr. Oct 2004 B2
6820801 Kaneko Nov 2004 B2
6841963 Song Jan 2005 B2
6845297 Allard Jan 2005 B2
6850024 Peless Feb 2005 B2
6859010 Jeon Feb 2005 B2
6859976 Plankenhorn Mar 2005 B2
6860206 Rudakevych Mar 2005 B1
6868307 Song Mar 2005 B2
6869633 Sus Mar 2005 B2
6870792 Chiappetta Mar 2005 B2
6882334 Meyer Apr 2005 B1
6883201 Jones Apr 2005 B2
6885912 Peless Apr 2005 B2
6901624 Mod Jun 2005 B2
6925679 Wallach Aug 2005 B2
D510066 Hickey Sep 2005 S
6938298 Aasen Sep 2005 B2
6939208 Kamimura Sep 2005 B2
6940291 Ozick Sep 2005 B1
6941199 Bottomley Sep 2005 B1
6942548 Wada Sep 2005 B2
6956348 Landry Oct 2005 B2
6957712 Song Oct 2005 B2
6964312 Maggio Nov 2005 B2
6965209 Jones Nov 2005 B2
6967275 Ozick Nov 2005 B2
6971140 Kim Dec 2005 B2
6971141 Tak Dec 2005 B1
6984952 Peless Jan 2006 B2
7000623 Welsh Feb 2006 B2
7004269 Song Feb 2006 B2
7013200 Wakui Mar 2006 B2
7013527 Thomas, Sr. Mar 2006 B2
7015831 Karlsson Mar 2006 B2
7024278 Chiappetta Apr 2006 B2
7031805 Lee Apr 2006 B2
7040968 Kamimura May 2006 B2
7042342 Luo May 2006 B2
7043794 Conner May 2006 B2
7050926 Theurer et al. May 2006 B2
7053578 Diehl et al. May 2006 B2
7053580 Aldred May 2006 B2
7054716 McKee May 2006 B2
7059012 Song Jun 2006 B2
7079923 Abramson Jul 2006 B2
7082350 Skoog Jul 2006 B2
D526753 Tani Aug 2006 S
7085624 Aldred Aug 2006 B2
7103449 Woo Sep 2006 B2
7113847 Chmura Sep 2006 B2
7117067 McLurkin Oct 2006 B2
7133745 Wang Nov 2006 B2
7134164 Alton Nov 2006 B2
7135992 Karlsson Nov 2006 B2
7143696 Rudakevych Dec 2006 B2
7145478 Goncalves Dec 2006 B2
7150068 Ragner Dec 2006 B1
7155308 Jones Dec 2006 B2
7155309 Peless Dec 2006 B2
7162338 Goncalves Jan 2007 B2
7167775 Abramson Jan 2007 B2
7173391 Jones Feb 2007 B2
7174238 Zweig Feb 2007 B1
7177737 Karlsson Feb 2007 B2
7184586 Jeon Feb 2007 B2
7185396 Im Mar 2007 B2
7185397 Stuchlik Mar 2007 B2
7188000 Chiappetta Mar 2007 B2
7196487 Jones Mar 2007 B2
7199711 Field Apr 2007 B2
7200892 Kim Apr 2007 B2
7202630 Dan Apr 2007 B2
7206677 Hulden Apr 2007 B2
7207081 Gerber Apr 2007 B2
7208892 Tondra Apr 2007 B2
7213298 Cipolla May 2007 B2
7213663 Kim May 2007 B2
7222390 Cipolla May 2007 B2
7225500 Diehl Jun 2007 B2
7237298 Reindle Jul 2007 B2
7240396 Thomas, Sr. Jul 2007 B2
7246405 Yan Jul 2007 B2
7248951 Hulden Jul 2007 B2
7251853 Park Aug 2007 B2
7254464 McLurkin Aug 2007 B1
7254859 Gerber Aug 2007 B2
7269877 Tondra Sep 2007 B2
7272467 Goncalves Sep 2007 B2
7272868 Im Sep 2007 B2
7274167 Kim Sep 2007 B2
7275280 Haegermarck Oct 2007 B2
7288912 Landry Oct 2007 B2
D556961 Swyst Dec 2007 S
7303776 Sus Dec 2007 B2
7324870 Lee Jan 2008 B2
7331436 Pack Feb 2008 B1
7332890 Cohen Feb 2008 B2
7343221 Ann Mar 2008 B2
7343719 Sus Mar 2008 B2
7346428 Huffman Mar 2008 B1
7349759 Peless Mar 2008 B2
7359766 Jeon Apr 2008 B2
7363994 DeFazio Apr 2008 B1
7369460 Chiappetta May 2008 B2
7372004 Buchner May 2008 B2
7388343 Jones Jun 2008 B2
7389156 Ziegler Jun 2008 B2
7389166 Harwig Jun 2008 B2
7403360 Cunningham Jul 2008 B2
7412748 Lee Aug 2008 B2
7417404 Lee Aug 2008 B2
7418762 Arai Sep 2008 B2
7424766 Reindle Sep 2008 B2
7429843 Jones Sep 2008 B2
7430455 Casey Sep 2008 B2
7438766 Song Oct 2008 B2
7441298 Svendsen Oct 2008 B2
7444206 Abramson Oct 2008 B2
7448113 Jones Nov 2008 B2
7459871 Landry Dec 2008 B2
7464157 Okude Dec 2008 B2
7474941 Kim Jan 2009 B2
7480958 Song Jan 2009 B2
7480960 Kim Jan 2009 B2
D586959 Geringer Feb 2009 S
7489277 Sung Feb 2009 B2
7489985 Ko Feb 2009 B2
7499774 Barrett Mar 2009 B2
7499775 Filippov Mar 2009 B2
7499776 Allard Mar 2009 B2
7499804 Svendsen Mar 2009 B2
7503096 Lin Mar 2009 B2
7515991 Egawa Apr 2009 B2
D593265 Carr May 2009 S
7539557 Yamauchi May 2009 B2
7546891 Won Jun 2009 B2
7546912 Pack Jun 2009 B1
7555363 Augenbraun Jun 2009 B2
7556108 Won Jul 2009 B2
7559269 Rudakevych Jul 2009 B2
7564571 Karabassi Jul 2009 B2
7566839 Hukuba Jul 2009 B2
7567052 Jones Jul 2009 B2
7568259 Yan Aug 2009 B2
7568536 Yu Aug 2009 B2
7571511 Jones Aug 2009 B2
7573403 Goncalves Aug 2009 B2
7574282 Petersson Aug 2009 B2
7578020 Jaworski Aug 2009 B2
7579803 Jones Aug 2009 B2
7581282 Woo Sep 2009 B2
7597162 Won Oct 2009 B2
7600521 Woo Oct 2009 B2
7600593 Filippov Oct 2009 B2
7603744 Reindle Oct 2009 B2
7604675 Makarov Oct 2009 B2
7610651 Baek Nov 2009 B2
7613543 Petersson Nov 2009 B2
7620476 Morse Nov 2009 B2
7636982 Jones Dec 2009 B2
7647144 Haegermarck Jan 2010 B2
7650666 Jang Jan 2010 B2
7654348 Ohm Feb 2010 B2
7660650 Kawagoe Feb 2010 B2
7663333 Jones Feb 2010 B2
7673367 Kim Mar 2010 B2
7679532 Karlsson Mar 2010 B2
7688676 Chiappetta Mar 2010 B2
7693654 Dietsch Apr 2010 B1
7697141 Jones Apr 2010 B2
7706917 Chiappetta Apr 2010 B1
7706921 Jung Apr 2010 B2
7709497 Christensen, IV May 2010 B2
7711450 Im May 2010 B2
7720572 Ziegler May 2010 B2
7721829 Lee May 2010 B2
7729801 Abramson Jun 2010 B2
7749294 Oh Jul 2010 B2
7751940 Lee Jul 2010 B2
7761954 Ziegler Jul 2010 B2
7765635 Park Aug 2010 B2
7765638 Pineschi et al. Aug 2010 B2
7769490 Abramson Aug 2010 B2
7774158 Domingues Goncalves Aug 2010 B2
7779504 Lee Aug 2010 B2
7780796 Shim Aug 2010 B2
7784139 Sawalski Aug 2010 B2
7784570 Couture Aug 2010 B2
7785544 Alward Aug 2010 B2
7787991 Jeung Aug 2010 B2
7793614 Ericsson Sep 2010 B2
7801645 Taylor Sep 2010 B2
7805220 Taylor Sep 2010 B2
7827653 Liu Nov 2010 B1
7832048 Harwig Nov 2010 B2
7835529 Hernandez Nov 2010 B2
7843431 Robbins Nov 2010 B2
7844364 McLurkin Nov 2010 B2
7849555 Hahm Dec 2010 B2
7856291 Jung Dec 2010 B2
7860608 Lee Dec 2010 B2
7861365 Sun Jan 2011 B2
7861366 Hahm Jan 2011 B2
7873437 Aldred Jan 2011 B2
7877166 Harwig Jan 2011 B2
7886399 Dayton Feb 2011 B2
7890210 Choi Feb 2011 B2
7891045 Kim Feb 2011 B2
7891289 Day Feb 2011 B2
7891446 Couture Feb 2011 B2
7894951 Norris Feb 2011 B2
7916931 Lee Mar 2011 B2
7920941 Park Apr 2011 B2
7921506 Baek Apr 2011 B2
7926598 Rudakevych Apr 2011 B2
7934571 Chiu May 2011 B2
7937800 Yan May 2011 B2
7942107 Vosburgh May 2011 B2
7957837 Ziegler Jun 2011 B2
7962997 Chung Jun 2011 B2
7966339 Kim Jun 2011 B2
7975790 Kim Jul 2011 B2
7979175 Allard Jul 2011 B2
7979945 Dayton Jul 2011 B2
7981455 Sus Jul 2011 B2
7997118 Mecca Aug 2011 B2
8001651 Chang Aug 2011 B2
8007221 More Aug 2011 B1
8010229 Kim Aug 2011 B2
8019223 Hudson Sep 2011 B2
8020657 Allard Sep 2011 B2
8032978 Haegermarck Oct 2011 B2
8034390 Sus Oct 2011 B2
8042663 Pack Oct 2011 B1
8046103 Abramson Oct 2011 B2
8061461 Couture Nov 2011 B2
8065778 Kim Nov 2011 B2
8073439 Stromberg Dec 2011 B2
8074752 Rudakevych Dec 2011 B2
8078338 Pack Dec 2011 B2
8079432 Ohm Dec 2011 B2
8082836 More Dec 2011 B2
8086419 Goncalves Dec 2011 B2
8087117 Kapoor Jan 2012 B2
8095238 Jones Jan 2012 B2
8095336 Goncalves Jan 2012 B2
8107318 Chiappetta Jan 2012 B2
8108092 Phillips Jan 2012 B2
8109191 Rudakevych Feb 2012 B1
8112942 Bohm Feb 2012 B2
8113304 Won Feb 2012 B2
8122982 Morey Feb 2012 B2
8127396 Mangiardi Mar 2012 B2
8127399 Dilger Mar 2012 B2
8127704 Vosburgh Mar 2012 B2
8136200 Splinter Mar 2012 B2
8150650 Goncalves Apr 2012 B2
D659311 Geringer May 2012 S
8166904 Israel May 2012 B2
8195333 Ziegler Jun 2012 B2
8196251 Lynch Jun 2012 B2
8199109 Robbins Jun 2012 B2
8200600 Rosenstein Jun 2012 B2
8200700 Moore Jun 2012 B2
8237389 Fitch Aug 2012 B2
8237920 Jones Aug 2012 B2
8239992 Schnittman Aug 2012 B2
8244469 Cheung Aug 2012 B2
8253368 Landry Aug 2012 B2
8255092 Phillips Aug 2012 B2
8256542 Couture Sep 2012 B2
8265793 Cross Sep 2012 B2
8274406 Karlsson Sep 2012 B2
8281703 Moore Oct 2012 B2
8281731 Vosburgh Oct 2012 B2
8290619 McLurkin Oct 2012 B2
8292007 DeFazio Oct 2012 B2
8295125 Chiappetta Oct 2012 B2
D670877 Geringer Nov 2012 S
8308529 DAmbra Nov 2012 B2
8311674 Abramson Nov 2012 B2
8316971 Couture Nov 2012 B2
8318499 Fritchie Nov 2012 B2
D672928 Swett Dec 2012 S
8322470 Ohm Dec 2012 B2
8326469 Phillips Dec 2012 B2
8327960 Couture Dec 2012 B2
8336479 Vosburgh Dec 2012 B2
8342271 Filippov Jan 2013 B2
8347088 Moore Jan 2013 B2
8347444 Schnittman Jan 2013 B2
8350810 Robbins Jan 2013 B2
8353373 Rudakevych Jan 2013 B2
8364309 Bailey Jan 2013 B1
8364310 Jones Jan 2013 B2
8365848 Won Feb 2013 B2
8368339 Jones Feb 2013 B2
8370985 Schnittman Feb 2013 B2
8374721 Halloran Feb 2013 B2
8375838 Rudakevych Feb 2013 B2
8378613 Landry Feb 2013 B2
8380350 Ozick Feb 2013 B2
8382906 Konandreas Feb 2013 B2
8386081 Landry Feb 2013 B2
8387193 Ziegler Mar 2013 B2
8390251 Cohen Mar 2013 B2
8392021 Konandreas Mar 2013 B2
8396592 Jones Mar 2013 B2
8396611 Phillips Mar 2013 B2
8402586 Lavabre Mar 2013 B2
8408956 Vosburgh Apr 2013 B1
8412377 Casey Apr 2013 B2
8413752 Page Apr 2013 B2
8417188 Vosburgh Apr 2013 B1
8417383 Ozick Apr 2013 B2
8418303 Kapoor Apr 2013 B2
8418642 Vosburgh Apr 2013 B2
8428778 Landry Apr 2013 B2
8433442 Friedman Apr 2013 B2
D682362 Mozeika May 2013 S
8438694 Kim May 2013 B2
8438695 Gilbert, Jr. May 2013 B2
8438698 Kim May 2013 B2
8447440 Phillips May 2013 B2
8447613 Hussey May 2013 B2
8452448 Pack May 2013 B2
8453289 Lynch Jun 2013 B2
8456125 Landry Jun 2013 B2
8461803 Cohen Jun 2013 B2
8463438 Jones Jun 2013 B2
8473140 Norris Jun 2013 B2
8474090 Jones Jul 2013 B2
8478442 Casey Jul 2013 B2
8485330 Pack Jul 2013 B2
8505158 Han Aug 2013 B2
8508388 Karlsson Aug 2013 B2
8515578 Chiappetta Aug 2013 B2
8516651 Jones Aug 2013 B2
8525995 Jones Sep 2013 B2
8527113 Yamauchi Sep 2013 B2
8528157 Schnittman Sep 2013 B2
8528162 Tang Sep 2013 B2
8528673 More Sep 2013 B2
8532822 Abramson Sep 2013 B2
8533144 Reeser Sep 2013 B1
8534983 Schoenfeld Sep 2013 B2
8543562 Mule Sep 2013 B2
8548626 Steitz Oct 2013 B2
8551254 Dayton Oct 2013 B2
8551421 Luchinger Oct 2013 B2
8565920 Casey Oct 2013 B2
8572799 Won Nov 2013 B2
8584305 Won Nov 2013 B2
8584306 Chung Nov 2013 B2
8584307 Won Nov 2013 B2
8594840 Chiappetta Nov 2013 B1
8598829 Landry Dec 2013 B2
8599645 Chiappetta Dec 2013 B2
8600553 Svendsen Dec 2013 B2
8606401 Ozick Dec 2013 B2
8634956 Chiappetta Jan 2014 B1
8634958 Chiappetta Jan 2014 B1
8666523 Kim Mar 2014 B2
8671513 Yoo et al. Mar 2014 B2
8732895 Cunningham May 2014 B2
8741013 Swett et al. Jun 2014 B2
8743286 Hasegawa Jun 2014 B2
8745194 Uribe-Etxebarria Jimenez Jun 2014 B2
8755936 Friedman Jun 2014 B2
8761931 Halloran Jun 2014 B2
8763200 Kim Jul 2014 B2
8774970 Knopow Jul 2014 B2
8780342 DiBernardo et al. Jul 2014 B2
8798791 Li Aug 2014 B2
8798792 Park Aug 2014 B2
8799258 Mule Aug 2014 B2
8838274 Jones Sep 2014 B2
8839477 Schnittman Sep 2014 B2
8843245 Choe Sep 2014 B2
8855914 Alexander Oct 2014 B1
8874264 Chiappetta Oct 2014 B1
8880342 Ando et al. Nov 2014 B2
8881339 Gilbert, Jr. et al. Nov 2014 B2
8924042 Kim Dec 2014 B2
8961695 Romanov Feb 2015 B2
8985127 Konandreas Mar 2015 B2
8996172 Shah et al. Mar 2015 B2
9033079 Shin May 2015 B2
9037396 Pack May 2015 B2
9144361 Landry Sep 2015 B2
9360300 EnricoDiBernado Jun 2016 B2
9436185 Schnittman Sep 2016 B2
9687132 Schlischka Jun 2017 B2
10045675 Haegermarck Aug 2018 B2
20010004719 Sommer Jun 2001 A1
20010037163 Allard Nov 2001 A1
20020016649 Jones Feb 2002 A1
20020091466 Song Jul 2002 A1
20020108635 Marrero Aug 2002 A1
20020121288 Marrero Sep 2002 A1
20020121561 Marrero Sep 2002 A1
20020164932 Kamimura Nov 2002 A1
20020174506 Wallach Nov 2002 A1
20020185071 Guo Dec 2002 A1
20020189871 Won Dec 2002 A1
20030000034 Welsh Jan 2003 A1
20030025472 Jones Feb 2003 A1
20030030398 Jacobs Feb 2003 A1
20030120972 Matsushima Jun 2003 A1
20030159223 Plankenhorn Aug 2003 A1
20030167000 Mullick Sep 2003 A1
20030229421 Chmura Dec 2003 A1
20040020000 Jones Feb 2004 A1
20040031111 Porchia Feb 2004 A1
20040031121 Martin Feb 2004 A1
20040034952 Ho Feb 2004 A1
20040049877 Jones Mar 2004 A1
20040049878 Thomas Mar 2004 A1
20040074038 Im Apr 2004 A1
20040074039 Kim Apr 2004 A1
20040098167 Yi May 2004 A1
20040111184 Chiappetta Jun 2004 A1
20040111827 Im Jun 2004 A1
20040167667 Goncalves Aug 2004 A1
20040181896 Egawa Sep 2004 A1
20040182839 Denney Sep 2004 A1
20040182840 Denney Sep 2004 A1
20040185011 Alexander Sep 2004 A1
20040187249 Jones Sep 2004 A1
20040207355 Jones Oct 2004 A1
20040208212 Denney Oct 2004 A1
20040210343 Kim Oct 2004 A1
20040220707 Pallister Nov 2004 A1
20050010331 Taylor Jan 2005 A1
20050015912 Kim Jan 2005 A1
20050015915 Thomas Jan 2005 A1
20050028315 Thomas Feb 2005 A1
20050028316 Thomas Feb 2005 A1
20050042151 Alward Feb 2005 A1
20050065662 Reindle Mar 2005 A1
20050085947 MichaelAldred Apr 2005 A1
20050088643 Anderson Apr 2005 A1
20050156562 Cohen Jul 2005 A1
20050166354 NaoyaUehigashi Aug 2005 A1
20050191949 Kamimura Sep 2005 A1
20050217061 Reindle Oct 2005 A1
20050223514 Stuchlik Oct 2005 A1
20050229340 Sawalski Oct 2005 A1
20050230166 Petersson Oct 2005 A1
20050234611 Uehigashi Oct 2005 A1
20050251292 Casey Nov 2005 A1
20050251457 Kashiwagi Nov 2005 A1
20050251947 Lee Nov 2005 A1
20050267629 Petersson Dec 2005 A1
20050278888 Reindle Dec 2005 A1
20050287038 Dubrovsky Dec 2005 A1
20060009879 Lynch Jan 2006 A1
20060010799 Bohm Jan 2006 A1
20060020369 Taylor Jan 2006 A1
20060020370 Abramson Jan 2006 A1
20060028306 Hukuba Feb 2006 A1
20060032013 Kim Feb 2006 A1
20060045981 Tsushi Mar 2006 A1
20060076039 Song et al. Apr 2006 A1
20060095158 Lee May 2006 A1
20060136096 Chiappetta Jun 2006 A1
20060144834 Denney Jul 2006 A1
20060178777 Park Aug 2006 A1
20060190133 Konandreas Aug 2006 A1
20060190134 Ziegler Aug 2006 A1
20060190146 Morse Aug 2006 A1
20060195015 Mullick Aug 2006 A1
20060200281 Ziegler Sep 2006 A1
20060213025 Sawalski Sep 2006 A1
20060235570 Jung Oct 2006 A1
20060235585 HirotoTanaka Oct 2006 A1
20060236492 KazuyaSudo Oct 2006 A1
20060288519 Jaworski Dec 2006 A1
20060293788 Pogodin Dec 2006 A1
20070016328 Ziegler Jan 2007 A1
20070021867 Woo Jan 2007 A1
20070059441 Greer Mar 2007 A1
20070061040 Augenbraun et al. Mar 2007 A1
20070114975 Cohen May 2007 A1
20070118248 Lee et al. May 2007 A1
20070124890 Erko Jun 2007 A1
20070143950 Lin Jun 2007 A1
20070156286 Yamauchi Jul 2007 A1
20070179670 Chiappetta Aug 2007 A1
20070189347 Denney Aug 2007 A1
20070204426 Nakagawa Sep 2007 A1
20070213892 Jones Sep 2007 A1
20070214601 Chung Sep 2007 A1
20070234492 Svendsen Oct 2007 A1
20070244610 Ozick Oct 2007 A1
20070250212 Halloran et al. Oct 2007 A1
20070266508 Jones Nov 2007 A1
20070267230 Won Nov 2007 A1
20070267570 Park Nov 2007 A1
20070267998 Cohen Nov 2007 A1
20070273864 Cho Nov 2007 A1
20070276541 Sawasaki Nov 2007 A1
20070285041 Jones Dec 2007 A1
20070289267 Makarov Dec 2007 A1
20070290649 Jones Dec 2007 A1
20080000041 Jones Jan 2008 A1
20080000042 Jones Jan 2008 A1
20080001566 Jones Jan 2008 A1
20080007203 Cohen Jan 2008 A1
20080009964 Bruemmer et al. Jan 2008 A1
20080015738 Casey Jan 2008 A1
20080016631 Casey Jan 2008 A1
20080037170 Saliba Feb 2008 A1
20080039974 Sandin Feb 2008 A1
20080047092 Schnittman Feb 2008 A1
20080051953 Jones Feb 2008 A1
20080007193 Bow Mar 2008 A1
20080052846 Kapoor Mar 2008 A1
20080058987 Ozick Mar 2008 A1
20080063400 Hudson Mar 2008 A1
20080065265 Ozick Mar 2008 A1
20080077278 Park Mar 2008 A1
20080084174 Jones Apr 2008 A1
20080086241 Phillips Apr 2008 A1
20080091304 Ozick Apr 2008 A1
20080091305 Svendsen Apr 2008 A1
20080093131 Couture Apr 2008 A1
20080098553 Dayton May 2008 A1
20080105445 Dayton May 2008 A1
20080109126 Sandin May 2008 A1
20080121097 Rudakevych May 2008 A1
20080127445 Konandreas Jun 2008 A1
20080127446 Ziegler Jun 2008 A1
20080133052 Jones Jun 2008 A1
20080134457 Morse Jun 2008 A1
20080134458 Ziegler Jun 2008 A1
20080140255 Ziegler Jun 2008 A1
20080143063 Won Jun 2008 A1
20080143064 Won Jun 2008 A1
20080143065 DeFazio Jun 2008 A1
20080152871 Greer Jun 2008 A1
20080155768 Ziegler Jul 2008 A1
20080179115 Ohm Jul 2008 A1
20080183332 Ohm Jul 2008 A1
20080184518 Taylor Aug 2008 A1
20080196946 Filippov Aug 2008 A1
20080205194 Chiappetta Aug 2008 A1
20080209665 Mangiardi Sep 2008 A1
20080221729 ErwannLavarec Sep 2008 A1
20080223630 Couture Sep 2008 A1
20080235897 Kim Oct 2008 A1
20080236907 Won Oct 2008 A1
20080264456 Lynch Oct 2008 A1
20080266254 Robbins Oct 2008 A1
20080276407 Schnittman Nov 2008 A1
20080276408 Gilbert Nov 2008 A1
20080281470 Gilbert Nov 2008 A1
20080282494 Won Nov 2008 A1
20080294288 Yamauchi Nov 2008 A1
20080307590 Jones Dec 2008 A1
20090007366 Svendsen Jan 2009 A1
20090025155 Nishiyama Jan 2009 A1
20090030551 Hein et al. Jan 2009 A1
20090037024 Jamieson Feb 2009 A1
20090038089 Landry Feb 2009 A1
20090044370 Won Feb 2009 A1
20090045766 Casey Feb 2009 A1
20090055022 Casey Feb 2009 A1
20090065271 Won Mar 2009 A1
20090070946 Tamada Mar 2009 A1
20090078035 Mecca Mar 2009 A1
20090107738 Won Apr 2009 A1
20090125175 Park May 2009 A1
20090126143 Haegermarck May 2009 A1
20090133720 Vandenbogert May 2009 A1
20090145671 Filippov Jun 2009 A1
20090173553 Won Jul 2009 A1
20090180668 Jones Jul 2009 A1
20090226113 Matsumoto Sep 2009 A1
20090232506 Hudson Sep 2009 A1
20090241826 Vosburgh Oct 2009 A1
20090254217 Pack Oct 2009 A1
20090254218 Sandin Oct 2009 A1
20090265036 Jamieson Oct 2009 A1
20090270015 DAmbra Oct 2009 A1
20090274602 Alward Nov 2009 A1
20090281661 Dooley et al. Nov 2009 A1
20090292393 Casey Nov 2009 A1
20090292884 Wang Nov 2009 A1
20090314318 Chang Dec 2009 A1
20090314554 Couture Dec 2009 A1
20090319083 Jones Dec 2009 A1
20100001478 DeFazio Jan 2010 A1
20100011529 Won Jan 2010 A1
20100037418 Hussey Feb 2010 A1
20100049364 Landry Feb 2010 A1
20100049365 Jones Feb 2010 A1
20100049391 Nakano Feb 2010 A1
20100063628 Landry Mar 2010 A1
20100075054 Kaneyama Mar 2010 A1
20100076600 Cross Mar 2010 A1
20100078415 Denney Apr 2010 A1
20100082193 Chiappetta Apr 2010 A1
20100107355 Won May 2010 A1
20100108098 Splinter May 2010 A1
20100115716 Landry May 2010 A1
20100116566 Ohm May 2010 A1
20100125968 Ho May 2010 A1
20100139029 Kim Jun 2010 A1
20100139995 Rudakevych Jun 2010 A1
20100161225 Hyung et al. Jun 2010 A1
20100173070 Niu Jul 2010 A1
20100206336 Souid Aug 2010 A1
20100217436 Jones Aug 2010 A1
20100257690 Jones Oct 2010 A1
20100257691 Jones Oct 2010 A1
20100263142 Jones Oct 2010 A1
20100263158 Jones Oct 2010 A1
20100268384 Jones Oct 2010 A1
20100275405 Morse Nov 2010 A1
20100286791 Goldsmith Nov 2010 A1
20100305752 Abramson Dec 2010 A1
20100312429 Jones Dec 2010 A1
20100313910 Lee Dec 2010 A1
20100313912 Han Dec 2010 A1
20110000363 More Jan 2011 A1
20110004339 Ozick Jan 2011 A1
20110010873 Kim Jan 2011 A1
20110077802 Halloran Mar 2011 A1
20110082668 Escrig Apr 2011 A1
20110088609 Vosburgh Apr 2011 A1
20110109549 Robbins May 2011 A1
20110125323 Gutmann et al. May 2011 A1
20110131741 Jones Jun 2011 A1
20110154589 Reindle Jun 2011 A1
20110202175 Romanov Aug 2011 A1
20110209726 Dayton Sep 2011 A1
20110252594 Blouin Oct 2011 A1
20110258789 Lavabre Oct 2011 A1
20110271469 Ziegler Nov 2011 A1
20110277269 Kim Nov 2011 A1
20110286886 Luchinger Nov 2011 A1
20110288684 Farlow Nov 2011 A1
20120011668 Schnittman Jan 2012 A1
20120011669 Schnittman Jan 2012 A1
20120011676 Jung Jan 2012 A1
20120011677 Jung Jan 2012 A1
20120011992 Rudakevych Jan 2012 A1
20120036659 Ziegler Feb 2012 A1
20120047676 Jung Mar 2012 A1
20120049798 Cohen Mar 2012 A1
20120079670 Yoon Apr 2012 A1
20120083924 Jones Apr 2012 A1
20120084934 Li Apr 2012 A1
20120084937 Won Apr 2012 A1
20120084938 Fu Apr 2012 A1
20120085368 Landry Apr 2012 A1
20120090133 Kim Apr 2012 A1
20120095619 Pack Apr 2012 A1
20120096656 Jung Apr 2012 A1
20120097783 Pack Apr 2012 A1
20120101661 Phillips Apr 2012 A1
20120102670 Jang May 2012 A1
20120109423 Pack May 2012 A1
20120110755 Liu May 2012 A1
20120118216 Vosburgh May 2012 A1
20120125363 Kim May 2012 A1
20120137464 Thatcher Jun 2012 A1
20120137949 Vosburgh Jun 2012 A1
20120151709 Tang Jun 2012 A1
20120152280 Bosses Jun 2012 A1
20120152877 Tadayon Jun 2012 A1
20120159725 Kapoor Jun 2012 A1
20120166024 Phillips Jun 2012 A1
20120167917 Gilbert Jul 2012 A1
20120169497 Schnittman Jul 2012 A1
20120173018 Allen Jul 2012 A1
20120173070 Schnittman Jul 2012 A1
20120180254 Morse Jul 2012 A1
20120180712 Vosburgh Jul 2012 A1
20120181099 Moon Jul 2012 A1
20120182392 Kearns Jul 2012 A1
20120183382 Couture Jul 2012 A1
20120185091 Field Jul 2012 A1
20120185094 Rosenstein Jul 2012 A1
20120185095 Rosenstein Jul 2012 A1
20120185096 Rosenstein Jul 2012 A1
20120192898 Lynch Aug 2012 A1
20120194395 Williams Aug 2012 A1
20120197439 Wang Aug 2012 A1
20120197464 Wang Aug 2012 A1
20120199006 Swett Aug 2012 A1
20120199407 Morey Aug 2012 A1
20120200149 Rudakevych Aug 2012 A1
20120222224 Yoon Sep 2012 A1
20120246862 Landry Oct 2012 A1
20120260443 Lindgren Oct 2012 A1
20120260861 Lindgren Oct 2012 A1
20120261204 Won Oct 2012 A1
20120265346 Gilbert Oct 2012 A1
20120265391 Letsky Oct 2012 A1
20120268587 Robbins Oct 2012 A1
20120281829 Rudakevych Nov 2012 A1
20120298029 Vosburgh Nov 2012 A1
20120303160 Ziegler Nov 2012 A1
20120311810 Gilbert Dec 2012 A1
20120312221 Vosburgh Dec 2012 A1
20120317745 Jung Dec 2012 A1
20120322349 Josi Dec 2012 A1
20130015596 Mozeika Jan 2013 A1
20130025085 Kim Jan 2013 A1
20130031734 Porat Feb 2013 A1
20130032078 Yahnker Feb 2013 A1
20130035793 Neumann Feb 2013 A1
20130047368 Tran Feb 2013 A1
20130054029 Huang Feb 2013 A1
20130054129 Wong Feb 2013 A1
20130060357 Li Mar 2013 A1
20130060379 Choe Mar 2013 A1
20130070563 Chiappetta Mar 2013 A1
20130081218 Kim Apr 2013 A1
20130085603 Chiappetta Apr 2013 A1
20130086760 Han Apr 2013 A1
20130092190 Yoon Apr 2013 A1
20130098402 Yoon et al. Apr 2013 A1
20130103194 Jones Apr 2013 A1
20130105233 Couture May 2013 A1
20130117952 Schnittman May 2013 A1
20130118524 Konandreas May 2013 A1
20130138246 Gutmann et al. May 2013 A1
20130138337 Pack May 2013 A1
20130145572 Schregardus Jun 2013 A1
20130152724 Mozeika Jun 2013 A1
20130160226 Lee Jun 2013 A1
20130166107 Robbins Jun 2013 A1
20130174371 Jones Jul 2013 A1
20130204463 Chiappetta Aug 2013 A1
20130204465 Phillips Aug 2013 A1
20130204483 Sung Aug 2013 A1
20130205520 Kapoor Aug 2013 A1
20130206170 Svendsen Aug 2013 A1
20130206177 Burlutskiy Aug 2013 A1
20130211589 Landry Aug 2013 A1
20130214498 DeFazio Aug 2013 A1
20130226344 Wong Aug 2013 A1
20130227801 Kim Sep 2013 A1
20130227812 Kim Sep 2013 A1
20130228198 Hung Sep 2013 A1
20130228199 Hung Sep 2013 A1
20130231779 Purkayastha Sep 2013 A1
20130231819 Hung Sep 2013 A1
20130232702 Baek Sep 2013 A1
20130239870 Hudson Sep 2013 A1
20130241217 Hickey Sep 2013 A1
20130253701 Halloran Sep 2013 A1
20130256042 Rudakevych Oct 2013 A1
20130268118 Grinstead Oct 2013 A1
20130269148 Chiu Oct 2013 A1
20130273252 Miyamoto Oct 2013 A1
20130298350 Schnittman Nov 2013 A1
20130310978 Ozick Nov 2013 A1
20130317944 Huang et al. Nov 2013 A1
20130325178 Jones Dec 2013 A1
20130331987 Karlsson Dec 2013 A1
20130338525 Allen Dec 2013 A1
20130338828 Chiappetta Dec 2013 A1
20130338831 Noh Dec 2013 A1
20130340201 Jang et al. Dec 2013 A1
20140016469 Ho Jan 2014 A1
20140026339 Konandreas Jan 2014 A1
20140053351 Kapoor Feb 2014 A1
20140109339 Won Apr 2014 A1
20140123325 Jung May 2014 A1
20140130272 Won May 2014 A1
20140142757 Ziegler May 2014 A1
20140167931 Lee Jun 2014 A1
20140180968 Song Jun 2014 A1
20140184144 Henricksen et al. Jul 2014 A1
20140207280 Duffley Jul 2014 A1
20140207281 Angle Jul 2014 A1
20140207282 Angle Jul 2014 A1
20140238440 Dayton Aug 2014 A1
20140249671 Halloran Sep 2014 A1
20140283326 Song Sep 2014 A1
20150005937 Ponulak Jan 2015 A1
20150032259 Kim Jan 2015 A1
20150039127 Matsumoto Feb 2015 A1
20150057800 Cohen Feb 2015 A1
20150120056 Noh et al. Apr 2015 A1
20150185322 Haegermarck Jul 2015 A1
20150197012 Schnittman Jul 2015 A1
20150206015 Ramalingam Jul 2015 A1
20150265122 Han et al. Sep 2015 A1
20160202703 Matsubara Jul 2016 A1
20160298970 Lindhe et al. Oct 2016 A1
20160306359 MagnusLindhe Oct 2016 A1
20160316982 Kim et al. Nov 2016 A1
20170273521 Klintemyr et al. Sep 2017 A1
20170273524 Klintemyr et al. Sep 2017 A1
20170344013 Haegermarck et al. Nov 2017 A1
20180103812 Lee et al. Apr 2018 A1
Foreign Referenced Citations (167)
Number Date Country
2154758 Jun 1995 CA
1116818 Feb 1996 CN
1668238 Sep 2005 CN
1883889 Dec 2006 CN
101161174 Apr 2008 CN
101297267 Oct 2008 CN
102083352 Jun 2011 CN
102183959 Sep 2011 CN
103027634 Apr 2013 CN
103054516 Apr 2013 CN
103308050 Sep 2013 CN
103376801 Oct 2013 CN
103491838 Jan 2014 CN
103534659 Jan 2014 CN
103565373 Feb 2014 CN
3536907 Apr 1986 DE
9307500 Jul 1993 DE
4211789 Oct 1993 DE
4340367 Jun 1995 DE
4439427 May 1996 DE
19849978 May 2000 DE
202008017137 Mar 2009 DE
102010000174 Jul 2011 DE
102010000573 Sep 2011 DE
102010037672 Mar 2012 DE
1447943 Sep 1976 EP
0142594 May 1985 EP
0358628 Mar 1990 EP
0474542 Mar 1992 EP
0584200 Apr 1993 EP
0569984 Nov 1993 EP
064133 Jan 1994 EP
0606173 Jul 1994 EP
075922 Jan 1995 EP
2355523 Apr 2001 EP
2382251 May 2003 EP
1099143 Nov 2003 EP
1360922 Nov 2003 EP
1441271 Jul 2004 EP
1331537 Aug 2005 EP
2050380 Apr 2009 EP
1969438 Sep 2009 EP
1395888 May 2011 EP
2316322 May 2011 EP
2296005 Jun 2011 EP
2251757 Nov 2011 EP
2417894 Feb 2012 EP
2438843 Apr 2012 EP
2466411 Jun 2012 EP
2561787 Feb 2013 EP
2494446 Mar 2013 EP
2578125 Apr 2013 EP
2583609 Apr 2013 EP
2604163 Jun 2013 EP
2447800 Apr 2014 EP
2741483 Jun 2014 EP
2999410 Jun 2014 EP
2772815 Sep 2014 EP
2884364 Jun 2015 EP
2992803 Mar 2016 EP
0584210 Apr 1993 FR
0759695 Mar 1995 GB
0944240 Feb 1997 GB
5540959 Mar 1980 JP
6286414 Apr 1987 JP
62109528 May 1987 JP
62120510 Jun 1987 JP
62152421 Jul 1987 JP
62152424 Jul 1987 JP
63127310 May 1988 JP
63181727 Jul 1988 JP
63241610 Oct 1988 JP
03162814 Jul 1991 JP
03166074 Jul 1991 JP
04260905 Sep 1992 JP
05084200 Apr 1993 JP
05189041 Jul 1993 JP
05224745 Sep 1993 JP
05228090 Sep 1993 JP
0683442 Mar 1994 JP
06125861 May 1994 JP
06144215 May 1994 JP
06179145 Jun 1994 JP
0732752 Apr 1995 JP
07129239 May 1995 JP
07281742 Oct 1995 JP
07287617 Oct 1995 JP
08326025 Dec 1996 JP
09150741 Jun 1997 JP
09185410 Jul 1997 JP
11267074 Oct 1999 JP
2001022443 Jan 2001 JP
2001187009 Jul 2001 JP
2002182742 Jun 2002 JP
2002287824 Oct 2002 JP
2002533797 Oct 2002 JP
2002355204 Dec 2002 JP
2002366228 Dec 2002 JP
2003505127 Feb 2003 JP
2003280740 Oct 2003 JP
2004096253 Mar 2004 JP
2004166968 Jun 2004 JP
2004198212 Jul 2004 JP
2004303134 Oct 2004 JP
2005040597 Feb 2005 JP
2005050105 Feb 2005 JP
2005124753 May 2005 JP
2005141636 Jun 2005 JP
2005314116 Nov 2005 JP
2006015113 Jan 2006 JP
2006087507 Apr 2006 JP
2006185438 Jul 2006 JP
2006231477 Sep 2006 JP
2006314669 Nov 2006 JP
2007014369 Jan 2007 JP
2007070658 Mar 2007 JP
2007143645 Jun 2007 JP
2007213236 Aug 2007 JP
2007226322 Sep 2007 JP
2007272665 Oct 2007 JP
2008132299 Jun 2008 JP
2008146617 Jun 2008 JP
2008290184 Dec 2008 JP
2008543394 Dec 2008 JP
2009500741 Jan 2009 JP
2009509220 Mar 2009 JP
2009193240 Aug 2009 JP
2010507169 Mar 2010 JP
2010079869 Apr 2010 JP
2010526594 Aug 2010 JP
2010534825 Nov 2010 JP
2011045694 Mar 2011 JP
2011253361 Dec 2011 JP
2012216051 Nov 2012 JP
2013041506 Feb 2013 JP
2013089256 May 2013 JP
2013247986 Dec 2013 JP
2014023930 Feb 2014 JP
20040096253 Nov 2004 KR
20050003112 Jan 2005 KR
20070070658 Jul 2007 KR
20090028359 Mar 2009 KR
101231932 Mar 2013 KR
7408667 Jan 1975 NL
8804081 Jun 1988 WO
9303399 Feb 1993 WO
9638770 Dec 1996 WO
0036961 Jun 2000 WO
0036970 Jun 2000 WO
0038025 Jun 2000 WO
0182766 Nov 2001 WO
03022120 Mar 2003 WO
03024292 Mar 2003 WO
03026474 Apr 2003 WO
2004006034 Jan 2004 WO
2004082899 Sep 2004 WO
2007008148 Jan 2007 WO
2007028049 Mar 2007 WO
2007051972 May 2007 WO
2007065034 Jun 2007 WO
2008048260 Apr 2008 WO
2009132317 Oct 2009 WO
2013105431 Jul 2013 WO
2013157324 Oct 2013 WO
2014033055 Mar 2014 WO
2014151501 Sep 2014 WO
2015016580 Feb 2015 WO
Non-Patent Literature Citations (138)
Entry
International Search Report and Written Opinion for International Application No. PCT/EP2016/055547, dated Jan. 2, 2017, 10 pages.
Notice of Allowance for U.S. Appl. No. 15/100,667, dated Aug. 6, 2018, 10 pages.
Non Final Office Action for U.S. Appl. No. 15/101,510, dated Jul. 27, 2018, 17 pages.
Non Final Office Action for U.S. Appl. No. 14/784,110, dated Aug. 16, 2018, 13 pages.
Chinese Office Action for Chinese Application No. 201380081537.9, dated Jun. 4, 2018 with translation, 15 pages.
Chinese Office Action for Chinese Application No. 201380075503.9, dated Nov. 8, 2017 with translation, 16 pages.
European Communication Pursuant to Article 94(3) for European Application No. 16176479.0, dated Nov. 27, 2017, 6 pages.
International Search Report and Written Opinion for International Application No. PCT/EP2015/070140, dated May 27, 2016, 11 pages.
European Communication Pursuant to Article 94(3) for European Application No. 13817911.4, dated Jan. 15, 2018, 8 pages.
Non Final Office Action for U.S. Appl. No. 15/102,017, dated Feb. 16, 2018, 12 pages.
Final Office Action for U.S. Appl. No. 15/102,017, dated Jun. 14, 2018, 12 pages.
Non Final Office Action for U.S. Appl. No. 15/101,235, dated Jun. 14, 2018, 11 pages.
Chinese Office Action for Chinese Application No. 201380081331.6, dated Mar. 26, 2018 with translation, 27 pages.
Decision of Refusal for Japanese Application No. 2016-526945, dated May 15, 2018 with translation, 5 pages.
Decision of Refusal for Japanese Application No. 2016-526875, dated May 15, 2018 with translation, 6 pages.
Notification of Reasons for Refusal for Japanese Application No. 2016-526765, dated May 15, 2018 with translation, 6 pages.
Non Final Office Action for U.S. Appl. No. 15/101,235, dated Nov. 1, 2017, 11 pages.
Non Final Office Action for U.S. Appl. No. 15/100,667, dated Nov. 29, 2017, 22 pages.
Non Final Office Action for U.S. Appl. No. 14/784,106, dated Oct. 19, 2017, 11 pages.
Final Office Action for U.S. Appl. No. 15/101,212, dated Oct. 11, 2017, 7 pages.
Chinese Office Action for Chinese Application No. 201380075510.9, dated Oct. 27, 2017 with translation, 13 pages.
Notification of Reasons for Refusal for Japanese Application No. 2016-526945, dated Oct. 31, 2017 with translation, 8 pages.
Notification of Reasons for Refusal for Japanese Application No. 2016-526875, dated Oct. 31, 2017 with translation, 10 pages.
Notice of Reasons for Rejection for Japanese Application No. 2016-526947, dated Sep. 21, 2017 with translation, 8 pages.
Notice of Allowance for U.S. Appl. No. 15/102,015, dated Dec. 11, 2017, 8 pages.
Non Final Office Action for U.S. Appl. No. 15/101,515, dated Apr. 18, 2018, 14 pages.
Notice of Allowance for U.S. Appl. No. 15/101,212, dated Apr. 11, 2018, 9 pages.
Final Office Action for U.S. Appl. No. 14/784,106, dated Mar. 28, 2018, 8 pages.
Final Office Action for U.S. Appl. No. 15/100,667, dated Mar. 27, 2018, 22 pages.
Notification of Reasons for Refusal for Japanese Application No. 2017-501374, dated Mar. 6, 2018 with translation, 8 pages.
Chinese Office Action for Chinese Application No. 201380081535.X, dated Mar. 26, 2018 with translation, 18 pages.
Chinese Office Action for Chinese Application No. 201380081103.9, dated Feb. 27, 2018 with translation, 19 pages.
Extended European Search Report for European Application No. 18157403.9, dated Nov. 14, 2018, 12 pages.
Report of Reconsideration by Examiner before Appeal for Japanese Application No. 2016-526875, dated Oct. 24, 2018, 2 pages.
Final Office Action for U.S. Appl. No. 15/101,235, dated Jan. 11, 2019, 12 pages.
Notice of Allowance for U.S. Appl. No. 14/409,291, dated Sep. 18, 2017, 8 pages.
Notice of Reasons for Rejection for Japanese Application No. 2016-526764, dated Aug. 25, 2017 with translation, 6 pages.
Notification to Reasons for Rejection for Japanese Application No. 2016-526765, dated Aug. 25, 2017 with translation, 7 pages.
Notification of Reasons for Refusal for Japanese Application No. 2016-526756, dated Aug. 10, 2017 with translation, 6 pages.
Notification of Reasons for Refusal for Japanese Application No. 2016-526759, dated Aug. 24, 2017 with translation, 9 pages.
Notice of Allowance for U.S. Appl. No. 14/784,106, dated Oct. 11, 2018 7 pages.
Non Final Office Action for U.S. Appl. No. 15/321,333, dated Oct. 24, 2018, 10 pages.
Position_ Definition of Position by Merriam-Webster.pdf (Position | Definition of Position by Merriam-Webster, Oct. 16, 2018, Merriam-Webster, https://www.merriam-webster.com/dictionary/position, pp. 1-15.
Gutman et al., AMOS: Comparison of Scan Matching Approaches for Self-Localization in Indoor Environments, 1996, IEEE, pp. 61-67.
Non Final Office Action for U.S. Appl. No. 15/504,071, dated Nov. 2, 2018, 17 pages.
Notification of Reasons for Refusal of Japanese Application No. 2016-568949, dated Oct. 1, 2018 with translation, 6 pages.
Non Final Office Action for U.S. Appl. No. 15/504,066, dated Nov. 5, 2018, 18 pages.
“SM51 Series Opposed Mode Sensors, DC sensors with metal housings: SM51EB/RB, SM51EB6/RB6”, Banner Engineering Corporation, pp. 1-24.
Andersson, et al., “ISR: An Intelligent Service Robot”, Centre for Autonomous Systems, Royal Institute of Technology, S-100 44 Stockholm, Sweden, pp. 1-24.
Berlin, et al. “Development of a Multipurpose Mobile Robot for Concrete Surface Processing”, A Status Report, Feb. 1992, Sweden, pp. 1-10.
Borenstein, et al. “Real-Time Obstacle Avoidance for Fast Mobile Robots”, IEEE, Jan. 6, 1996, pp. 1-18.
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, pp. 1-9.
Caselli, et al. “Mobile Robot Navigation in Enclosed Large-Scale Space”, Italy and U.S.A., pp. 1-5.
Cassens, et al. “Finishing and Maintaining Wood Floors”, Wood Finishing, North Central Regional Extension Publication #136, pp. 1-8.
Chinese Office Action for Chinese Application No. 20130075510.9, dated Feb. 6, 2017 with translation, 14pages.
Chinese Office Action for Chinese Application No. 201380075503.9, dated Febraury 13, 2017 with translation, 18 pages.
Chung etal.,“Path Planning for a Mobile Robot With Grid Type World Model”, Proceedings of the 1992 IEEE/RSJ International Conference on Intelligent Robots and Systems , Jul. 7-10, 1992, pp. 439-444.
Collins, et al. “Cerebellar Control of a Line Following Robot”, Computer Science and Electrical Engineering Department, University of Queensland, St.Lucia, Queensland, 4072 A, pp. 1-6.
Doty, et al. “Sweep Strategies for a Sensory-Driven, Behavior-Based Vacuum Cleaning Agent”, 1993, Machine Intelligence Laboratory-Gainesville Florida, AAAI 1993 Fall Symposium Series—Research Triangle Park—Raleigh, NC, Oct. 22-24, 1993, pp. 1-6.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, 1995, Chapters 1 and 3, 70pages.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, Ltd., 1995, Chapters 15 and 16, 59pages.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, Ltd., 1995, Chapters 6, 7 and 10, 79pages.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, Ltd., 1995, Chapters, 4a nd 5, 68pages.
Everett, et al. “Survey of Collision Avoidance and Ranging Sensors for Mobile Robots”, Revision 1, Technical Report 1194, Dec. 1992, pp. 1-154.
Extended European Search Report for European Application No. 16176479.0, dated Nov. 11, 2016, 9pages.
Final Office Action for U.S. Appl. No. 14/409,291, dated Jun. 6, 2017, 21 pages.
Final Office Action for U.S. Appl. No. 15/100,667, dated Apr. 21, 2017, 26 pages.
Gavrilut, et al., “Wall-Following Method for an Autonomous Mobile Robot using Two IR Sensors”, 12th WSEAS International Conference on SYSTEMS, Heraklion, Greece, Jul. 22-24, 2008, ISBN: 978-960-6766-83-1, ISSN: 1790-2769, pp. 205-209.
Herbst, et al., “Micromouse Design Specifications”, Jun. 2, 1998, pp. 1-22.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077377, dated Jun. 21, 2016, 12 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077378, dated Jun. 21, 2016, 7 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077384, dated Jun. 21, 2016, 6 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077385, dated Jun. 21, 2016, 7 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077386, dated Jun. 21, 2016, 6 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077387, dated Jun. 21, 2016, 9 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077657, dated Jun. 21, 2016, 7 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP2013/077661, dated Jun. 21, 2016, 11 pages.
International Preliminary Report on Patentability for International Application No. PCT/EP203/077380, dated Jun. 21, 2016, 6 pages.
International Search Report and Written Opinion of the International Searching Authority fo rInternatonal Applicaion No. PCT/EP2014/0077142, dated Sep. 11, 2015, 8 pages.
International Search Report and Written Opinion of the International Searching Authority for *International Application No. PCT/EP2015/058377, dated Aug. 10, 2016, 15 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2014/069073, dated May 12, 2015, 10 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2012/077377, dated Nov. 6, 2014, 18 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077378, dated Apr. 9, 2014, 9 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077380, dated Jul. 28, 2014, 8 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077384, dated Aug. 14, 2016, 9 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077385, dated May 27, 2015, 9 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077386, dated Sep. 17, 2014, 9 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077387, dated Sep. 30, 2014, 12 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2013/077661, dated Jun. 10, 2014, 15 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2014/069074, dated May 11, 2015, 9 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2014/077549, dated Jul. 27, 2015, 9 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2014/077947, dated Jul. 11, 2016, 14 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2014/077954, dated Oct. 12, 2015, 19pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2014/078144, 7 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP32013/077657, dated Aug. 18, 2014, 10 pages.
International Search Report for International Application No. PCT/EP2013/057814 dated Dec. 20, 2013, 5pages.
International Search Report for International Application No. PCT/EP2013/057815 dated Apr. 12, 2014, 4 pages.
International Search Report for International Application No. PCT/EP2013/067500 dated Dec. 10, 2013, 4pages.
Japanese Office Action for Application for Japanese Application No. 2015-528969, dated Apr. 7, 2017 with translation, 4 pages.
Japanese Office Action for Japanese Application No. 2016-506794, dated Feb. 7, 2017 with translation, 10 pages.
Japanese Office Action for Japanese Application No. 2016-506795 , dated Feb. 7, 2017 with translation, 6 pages.
Jenkins, “Practical Requirements for a Domestic Vacuum-Cleaning Robot”, From: AAAI Technical Report FS-93-03., JRL Consulting, Menlo Park, California, pp. 85-90.
Jones et al., Mobile Robots Inspiration to Implementation, Second Edition, A.K. Peters, Ltd., 1999, Chapters 1 and 5, 72pages.
Jones etal., Mobile Robots Inspiration to Implementation, Second Edition, A.K. Peters ,Ltd., 1999, Chapters 6 and 9, 56pages.
Jones etal., Mobile Robots Inspiration to Implementation, Second Edition, A.K. Peters, Ltd., 1999, Chapters 10 and 11, 45pages.
Jung, et al. “Whisker Based Mobile Robot Navigation”, Wollongong, NSW 2500, Australia, pp. 1-8.
Krishna, et al., “Solving the Local Minima Problem for a Mobile Robot by Classification of Spatio-Temporal Sensory Sequences”, Journal of Robotic Systems 17 (10), 2000, pp. 549-564.
Kube, “A Minimal Infrared Obstacle Detection Scheme”, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada, The Robotics Practitioner, 2(2): 15-20, 1996, Oct. 23, 1998, pp. 1-8.
Larson, “RoboKent—a case study in man-machine interfaces” Industrial Robot, vol. 25 No. 2, 1998, pp. 95-100.
LeBouthillier, “W. Grey Walter and his Turtle Robots”, The Robot Builder, vol. Eleven No. Five, May 1999, RSSC POB 26044, Santa Ana, CA, pp. 1-8.
Maaref,etal.“Sensor-based navigation of a mobile robot in an indoor environment”, Robotics and Autonomous Systems, 2002, Elsevier, 18pages.
Michael Carsten Bosse, “Atlas: A Framework for Large Scale Automated Mapping and Localization”, Massachusetts Institute of Technology, Feb. 2004, Part 2, 67 pages.
Michael Carsten Bosse, “Atlas: A Framework for Large Scale Automated Mapping and Localization”, Massachusetts Institute of Technology, Feb. 2004, Part 1, 140 pages.
Non Final Office Action for U.S. Appl. No. 14/409,291, dated Dec. 28, 2016, 61pages.
Non Final Office Action for U.S. Appl. No. 15/100,667, dated Sep. 12, 2016, 24 pages.
Non Final Office Action for U.S. Appl. No. 15/101,212, dated May 17, 2017, 8 pages.
Non Final Office Action for U.S. Appl. No. 15/101,235 dated Apr. 21, 2017, 10 pages.
Non Final Office Action for U.S. Appl. No. 15/101,257, dated Feb. 10, 2017, 10 pages.
Non Final Office Action for U.S. Appl. No. 15/102,015, dated Aug. 17, 2017, 13 pages.
Notice of Allowance for U.S. Appl. No. 14/409,291, dated Jun. 16, 2016, 13 pages.
Notice of Allowance for U.S. Appl. No. 15/101,257, dated Jul. 6, 2017, 9 pages.
Oren, Reply to Office Action dated Jun. 23, 2014, U.S. Appl. No. 13/757,985, pp. 1-10.
Pack, et al., “Constructing a Wall-Follower Robot for a Senior Design Project”, 1996 ASEE Annual Conference Proceedings, Session 1532, pp. 1-7.
Saffiotti, “Fuzzy logic in Autonomous Robot Navigation”, a case study, Nov. 1995 Revised: Aug. 1997, IRIDIA, Universite Libre de Bruxelles, Belgium, , Technical Report TR/IRIDIA/ 9525, Cover page+pp. 1-14.
Written Opinion for International Application No. PCT/EP2013/067500 dated Dec. 10, 2013, 7pages.
Yamamoto, “SOZZY: A Hormone-Driven Autonomous Vacuum Cleaner”, From: AAAI Technical Report FS-93-03, Matasushita Research Institute, Tokyo, and MIT Artificial Intelligence laboratory, Massachusetts, pp. 116-124+Figure 9 and Figure 11.
Notice of Allowance for U.S. Appl. No. 15/102,295, dated Sep. 24, 2018, 9 pages.
Notice of Allowance for U.S. Appl. No. 15/101,515, dated Aug. 28, 2018, 11 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2016/060565, dated Feb. 15, 2017, 12 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/EP2016/060571, dated Feb. 7, 2017, 8 pages.
Non Final Office Action for U.S. Appl. No. 15/535,506, dated May 1, 2019, 16 pages.
Yoshida et al., “Online Motion Planning Using Path Deformation and Replanning”, 28th Annual Robot Society, 2011, vol. 29, No. 8, Chapter 3, pp. 716-725 with partial translation, 10 pages.
Japanese Notice of Reasons for Refusal for Japanese Application No. 2017-522557, dated Jun. 18, 2019, 6 pages.
International Search Report and Written Opinion of the International Searching Authority for International Application No. PCT/E2016/072291, dated Jun. 6, 2017, 11 pages.
Non Final Office Action for U.S. Appl. No. 15/102,017, dated Jan. 22, 2019, 15 pages.
Final Office Action for U.S. Appl. No. 15/101,510, dated Feb. 8, 2019, 16 pages.
Final Office Action for U.S. Appl. No. 15/535,506, dated Sep. 17, 2019, 11 pages.
Chinese Office Actio for Chinese Application No. 201480084065.7, dated Sep. 16, 2019 with translation, 16 pages.
Related Publications (1)
Number Date Country
20190004537 A1 Jan 2019 US