Robot positioning system

Information

  • Patent Grant
  • 9939529
  • Patent Number
    9,939,529
  • Date Filed
    Friday, August 23, 2013
    10 years ago
  • Date Issued
    Tuesday, April 10, 2018
    6 years ago
Abstract
A robot positioning system having a camera, a processing unit and at least a first line laser. The first line laser is arranged to illuminate a space by projecting vertical laser beams within field of view of the camera. The camera is arranged to record a picture of the space illuminated by the vertical laser beams, and the processing unit is arranged to extract, from the recorded picture, image data representing a line formed by the vertical laser beams being reflected against objects located within the space. The processing unit is further arranged to create, from the extracted line, a representation of the illuminated space along the projected laser lines, in respect of which the robot is positioned. Methods of positioning a robot are also provided.
Description

This application is a U.S. National Phase application of PCT International Application No. PCT/EP2013/067500, filed Aug. 23, 2013, and claims the benefit of Swedish Application No. SE 1200514-6, Aug. 27, 2012, both of which are incorporated herein by reference.


TECHNICAL FIELD

The present invention relates to a robot positioning system and a method of positioning a robot.


BACKGROUND

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


As an a example, robotic vacuum cleaners exist in the art with the capability of more or less autonomously vacuum cleaning a room in which furniture such as tables and chairs and other obstacles such as walls and stairs are located. Traditionally, these robotic vacuum cleaners have navigated a room by means of using e.g. ultrasound or light waves. Further, the robotic vacuum cleaners typically must be complemented with additional sensors, such as stair sensors, wall-tracking sensors and various transponders to perform accurately.


A large number of prior art robot vacuum cleaners use a technology referred to as Simultaneous Localization and Mapping (SLAM). SLAM is concerned with the problem of building a map of an unknown environment by a mobile robot while at the same time navigating the environment using the map. This is typically combined with a horizontally scanning laser for range measurement. Further, odometry is used to provide an approximate position of the robot as measured by the movement of the wheels of the robot.


U.S. 2002/0091466 discloses a mobile robot with a first camera directed toward the ceiling of a room for recognizing a base mark on the ceiling and a line laser for emitting a linear light beam toward an obstacle, a second camera for recognizing a reflective linear light beam from the obstacle. The line laser emits a beam in the form of straight line extending horizontally in front of the mobile robot.


SUMMARY

An object of the present invention is to solve, or at least mitigate these problems in the art and provide an improved robot positioning system.


This objective is attained in a first aspect of the present invention by a robot positioning system comprising a camera, a processing unit and at least a first line laser. The first line laser is arranged to illuminate a space by projecting vertical laser lines within field of view of the camera. The camera is arranged to record a picture of the space illuminated by the vertical laser lines, and the processing unit is arranged to extract, from the recorded picture, image data representing a line formed by the vertical laser lines being reflected against objects located within the space. The processing unit is further arranged to create, from the extracted line, a representation of the illuminated space along the projected laser lines, wherein the robot is positioned with respect to said representation.


This object is attained in a second aspect of the present invention by a method of positioning a robot. The method comprises the steps of illuminating a space with at least a first line laser projecting vertical laser lines within field of view of a camera, and recording, with the camera, a picture of the space illuminated by the vertical laser lines. Further, the method comprises the steps of extracting, from the recorded picture, image data representing a line formed by the vertical laser lines being reflected against objects located within the space, and creating, from the extracted line, a representation of the illuminated space along the projected laser lines, wherein the robot is positioned with respect to said representation.


Advantageously, the robot positioning system according to embodiments of the present invention creates a representation of the environment in which the system is set to operate by recording image data being a result of light reflected against objects located within the illuminated environment. A prior art positioning sensor normally executes thousands of measurements every second in order to produce large amounts of data that must be processed for positioning the robot on which the positioning sensor is arranged. To the contrary, the robot positioning system of the present invention executes an equal amount of measurements, but only uses a small amount of the resulting data for positioning. The robot positioning system of the present invention only considers image data recorded along a planar surface achieved by the vertical laser lines projected by the line laser. This difference compared to prior art positioning sensors is even more stressed in case the environment for which a representation is to be created contains many objects, since every small detail will be represented by processing a relatively small amount of image data. In contrast to many prior art robot positioning systems, no floor sensor is required for e.g. preventing the robot from accidentally falling down a stair.


Further advantageous is that the robot positioning system can be used to detect dust and debris in front of a robotic vacuum cleaner on which the positioning system can be arranged. Even small particles on the floor illuminated by the line lasers will reflect considerably more light then a clean floor and can easily be detected by recording variation of the reflected light.


Yet another advantage is that even without undertaking a complex analysis of the picture and building a complete representation of the environment, pixel/image data of a recorded picture can be used directly to detect obstacles, edges and walls. Each pixel can be regarded as an obstacle detector for a small point in space, and every pixel detecting laser light can easily be translated to how much further the robot can move until it hits an object. Thus, the robot positioning system according to embodiments of the present invention enables provision of accurate and relevant data to navigate past obstacles at close distance.


In a further embodiment of the present invention, the robot positioning system further comprises a second line laser arranged to illuminate the space within field of view of the camera by projecting vertical laser lines. In this particular embodiment, the process unit is arranged to extract, from the recorded picture, image data representing a respective line formed by the vertical laser lines of the first and second line laser being reflected against an object located in the space. Further, the processing unit is arranged to create, from the respective extracted line, a representation of the illuminated space along the projected laser lines of the first and second line laser.


Advantageously, in case of using two light sources, positioning accuracy is improved, and the recorded pictures will contain more information for facilitating the creation of a detailed representation of the environment in which the robot positioning system operates.


In a further embodiment of the present invention, the first and second line lasers are arranged on a respective side of the camera along an axis being perpendicular to an optical axis of the camera. Advantageously, with this arrangement, the respective line laser can be mounted as far as possible from the camera, thus illuminating a greatest possible space.


In yet another embodiment of the present invention, an optical filter is arranged at the camera, which optical filter is adapted to a wavelength of the light emitted by the first (and second) line laser. Advantageously, the camera can be made sensitive to the particular wavelength used by the line laser(s), thus only recording reflected light from the line lasers.


In one embodiment, the camera is a Complementary Metal Oxide Semiconductor (CMOS) camera.


In still another embodiment of the present invention, the robot positioning system is arranged to be rotatable around a vertical axis. This can be achieved by having the robot positioning system fixedly mounted to the robotic vacuum cleaner and rotating the vacuum cleaner, or by having the robot positioning system rotatably mounted to the robotic vacuum cleaner. Advantageously, the robot positioning system can be set to rotate and the camera will record pictures of the complete environment in which the vacuum cleaner is set to operate. A complete representation of the environment can thus be attained.


In yet another embodiment of the present invention, the robot navigation system further comprises a positioning system for estimating an instantaneous position of the robot positioning system. This is advantageous since an origin of coordinates can be established for each recorded picture, and thus ultimately for the created representation.


In a further embodiment of the present invention, the image data is mapped to a coordinate system of a sensor array of the camera. Advantageously, each image feature of a recorded picture can thus be associated with a unique coordinate by utilizing the sensor array coordinate system. The created representation will thus be associated with a coordinate system for facilitating positioning of the robotic vacuum cleaner.


It is noted that the invention relates to all possible combinations of features recited in the claims. Further features of, and advantages with, the present invention will become apparent when studying the appended claims and the following description. Those skilled in the art realize that different features of the present invention can be combined to create embodiments other than those described in the following.





BRIEF DESCRIPTION OF THE DRAWINGS

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



FIG. 1 shows a robot positioning system according to an embodiment of the present invention;



FIG. 2a shows a top view of a robotic vacuum cleaner being arranged with a robot positioning system according to an embodiment of the present invention;



FIG. 2b shows the top view of FIG. 2a with field of view of the camera indicated according to an embodiment of the present invention;



FIG. 2c shows a side view of a robotic vacuum cleaner arranged with a robot positioning system according to an embodiment of the present invention;



FIGS. 3a and 3b illustrate a procedure of creating a representation of the environment in which a robot operates by using the robot positioning system according to an embodiment of the present invention;



FIG. 4 shows a flowchart of a method of positioning a robot according to an embodiment of the present invention;



FIG. 5 shows a flowchart of a method of positioning a robot according to another embodiment of the present invention; and



FIG. 6 illustrates a robot positioning system according to a further embodiment of the present 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. It should be noted that the robot navigation system according to embodiments of the present invention uses SLAM for positioning. SLAM is well known in the art and will not be discussed in any further detail.



FIG. 1 shows a robot positioning system according to an embodiment of the present invention. The robot positioning system 10 comprises a chassis 11 in which a light detector 12 such as a CMOS camera is located as well as two light sources 13, 14 in the form of line lasers. The line lasers 13, 14 are arranged to project vertical laser lines within field of view of the CMOS camera 12. The CMOS camera 12 will repeatedly record pictures of the space illuminated by the two line lasers 13, 14 such that a representation of the illuminated space can be created for accurate positioning. It should be noted that in an embodiment of the present invention, the robot positioning system comprises a single light source. However, in case of using two light sources, positioning accuracy is improved, and the recorded pictures will contain more information for facilitating the creation of a detailed representation of the environment in which the robot positioning system operates. Throughout the description, the use of two line lasers will be described.


Data processing and derivation of a representation of the illuminated space is typically performed by a processing unit 15 embodied in the form of one or more microprocessors arranged to execute a respective computer program 16 downloaded to a suitable storage medium 17 associated with the microprocessor, such as a Random Access Memory (RAM), a Flash memory or a hard disk drive. The processing unit 15 is arranged to at least partly carry out the method according to embodiments of the present invention when the appropriate computer program 16 comprising computer-executable instructions is downloaded to the storage medium 17 and executed by the processing unit 15. The storage medium 17 may also be a computer program product comprising the computer program 16. Alternatively, the computer program may be transferred to the storage medium by means of a suitable computer program product, such as a floppy disk or a memory stick. As a further alternative, the computer program 16 may be downloaded to the storage medium 17 over a network. The processing unit 15 may alternatively be embodied in the form of an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), etc. It should further be noted that in case the robot positioning system 10 is integrated with a device such as a robotic vacuum cleaner, the robot positioning system may utilize the microprocessor already available in the vacuum cleaner.


The robot positioning system 10 is typically mounted onto an appliance such as a robotic vacuum cleaner or floor washer. When mounted onto a robotic appliance, the robot positioning system is in an embodiment of the present invention arranged such that it can rotate around a vertical axis. This can be achieved by having the robot positioning system 10 fixedly mounted to the robotic vacuum cleaner and rotating the vacuum cleaner, or by having the robot positioning system 10 rotatably mounted to the robotic vacuum cleaner.



FIG. 2a illustrates a top view of a robotic vacuum cleaner 20 being arranged with a robot positioning system according to an embodiment of the present invention, where the two line lasers 13, 14 each illuminate a space 21 being located in the field of view of the CMOS camera 12 by means of vertical laser lines 22, 23. The respective line laser 13, 14 should be mounted as far as possible from the CMOS camera 12, thus illuminating a greatest possible space 21. Further, the robot positioning system should be placed as high as possible on the robotic vacuum cleaner to create the best overview of the environment in which the robotic vacuum cleaner is to operate.


With a CMOS camera 12 and at least one line laser 13, 14, every picture taken with the camera can be used to create a representation of a part of the illuminated space along the emitted laser beams 22, 23. As the robot positioning system and/or the complete robotic vacuum cleaner onto which the robot positioning system is mounted moves and rotates, the camera 12 repeatedly takes pictures which contains information from which image data can be derived in order to create a representation of the environment located within the space 21 illuminated by the lasers. In an embodiment, rotating the robot positioning system 360 degrees while repeatedly taking pictures will create a plurality of pictures containing information in the form of image data from which an extremely detailed representation of the geometry of the environment can be created.


The CMOS camera 12 can also be used to locate beacons and transponders in the environment as long as they emit with the same wavelength as the laser.


Robotic vacuum cleaners must be capable of moving freely about a space and are thus battery-driven. It should be noted that there is no need for an active beacon on the charging station of the vacuum cleaner of the present invention, since the charging station can be identified and located by its shape or a specific reflecting pattern on its front.



FIG. 2b illustrates a top view of a robotic vacuum cleaner 20 being arranged with a robot positioning system according to an embodiment of the present invention, where the two line lasers 13, 14 each illuminate a space 21 being located in the field of view of the CMOS camera 12 by means of vertical laser lines 22, 23.


As in FIG. 2a, the first line laser 13 and the second line laser 14 are arranged on a respective side of the camera 12 along an axis being perpendicular to an optical axis of the camera. Further, as can be seen in FIGS. 2a and 2b, the line lasers 13, 14 are directed such that their respective laser beams 23, 22 intersect within the field of view of the camera 12. Typically, the intersection coincides with the optical axis of the camera 12.


Advantageously, directional configuration of the line lasers 13, 14 and field of view 24 of the camera 12 are arranged such that the width wC of the illuminated space 21 located within the field of view 24 of the camera 12 is greater than the width wR of the robotic vacuum cleaner 20. Hence, the line lasers 13, 14 are directed such that the camera 12 having a selected field of view 24 is able to capture an illuminated space 21 having a width wC greater than the width wR of the robotic vacuum cleaner 20. This is useful for detecting obstacles, since the robot 20 is able to perceive obstacles appearing at least along its complete width wR.



FIG. 2c illustrates a side view of the robotic vacuum cleaner 20 shown in FIGS. 2a and 2b arranged with a robot positioning system according to an embodiment of the present invention. In analogy with that set forth in connection to FIG. 2b, the directional configuration of the line lasers causing the laser beams 22, 23 and the field of view 24 of the camera 12 are advantageously arranged such that the height hC of the illuminated space 21 which is located within the field of view 24 of the camera 12 is greater than the height hR of the robotic vacuum cleaner 20. Hence, the line lasers are directed such that the camera 12 having a given field of view 24 is able to capture an illuminated space 21 having a height hC greater than the height hR of the robotic vacuum cleaner 20. Again, this is useful for detecting obstacles, since the robot 20 is able to perceive obstacles appearing at least along its complete height hR.


In a further embodiment of the present invention, the robot positioning system of the present invention comprises a dust sensor for detecting dust, debris and/or particles illuminated by the line lasers 13, 14. The dust sensor may in practice be implemented by the previously discussed microprocessor 15 executing an appropriate computer program for attaining dust sensing functionality in a robotic vacuum cleaner being equipped with robot positioning system. Thus, the line lasers 13, 14 illuminates a space 21 of which the camera records pictures. From these pictures, image data may be extracted clearly indicating the illuminated particles. In case the robotic vacuum cleaner encounters an area comprising particles, these will light up, and may thus be distinguished from a clean, particle-free floor by using image processing. The robotic vacuum cleaner may thus advantageously be controlled on the basis of this information. For instance, suction capacity may temporarily be increased when passing over an area comprising a great number of particles, or the vacuum cleaner may be controlled to go over the area a couple of times to ensure that all dust and debris are removed.


With reference to FIGS. 3a and 3b, an embodiment of the present invention will be described illustrating a procedure of creating a representation of the environment in which a robot operates by using the robot positioning system of the present invention, with respect to which representation the robot can be positioned. The line lasers 13, 14 are controlled to emit light to create a respective vertical laser line 22, 23, while the CMOS camera 12 is operated to repeatedly take pictures. In order to minimize detrimental effects of ambient light, the line lasers are optionally controlled to emit light at a highest possible effect. Further, an optical filter can be arranged in front of the CMOS camera to make the camera more perceptive to the light emitted by the line lasers.


The estimated position of the robot is recorded at the time of taking the respective picture by applying dead reckoning. This is a known method where a current position is calculated by using data pertaining to a previously determined position. Image data of each picture is filtered for noise reduction and a line defining the respective vertical laser lines is extracted using any appropriate edge detection method, such as e.g. the Canny edge detection algorithm. Since the respective line extracted from the image data may be grainy, image processing may be further enhanced by extracting the center of the laser lines present in the picture, using for instance the so called center of gravity method on adjacent pixel values in the respective edge detected laser line to calculate the center of the laser line.


Since a CMOS camera is equipped with a light sensor array, where each individual light sensor (i.e. pixel) in the array represents detected light from a unique position in space, a recorded picture will contain image data representing objects that the line lasers have illuminated, which image data further can be associated with unique coordinates. Subsequently, a list of coordinates where the center of the laser lines runs in the sensor array, i.e. in the recorded picture, is derived. Advantageously, these coordinates will have a much higher resolution then the picture pixels they were extracted from, since each laser line center coordinate is calculated from several pixels and the registered light in all those pixels.


With reference to FIGS. 3a and 3b, and the flowchart of FIG. 4 illustrating a method according to an embodiment of the present invention, as the robotic vacuum cleaner 20 moves about a room to be cleaned, the first and second line laser 13, 14 illuminates in step S101 the space 21 in a field of view of the CMOS camera 12 by means of vertical laser lines 22, 23, respectively. The camera 12 records, in step S102, pictures of the illuminated space 21. Thereafter, image data representing a line formed by the respective vertical laser lines 22, 23 are extracted in step S103 from the recorded picture(s), From these extracted line, a representation of the illuminated space along the projected laser lines is created in step S104 since the extracted lines can be associated with unique coordinates in the space 21. A first obstacle in the form of a threshold 31 and a second obstacle in the form of a wall 32 is illuminated by the line lasers. In FIG. 3b, since each individual light sensor of the CMOS camera 12 represents a unique position in space, a recorded picture contains image data which represents illuminated objects and their particular coordinates in the space 21. Thus, the representation of the illuminated space along the projected laser lines will appear as a cross section of the room along the planar surface formed by the emitted laser lines 22, 23. As can be seen the threshold 31 and the wall 32 can be found in FIG. 3b. Further, it can be calculated with high accuracy where the objects are located in the room. For instance, the distance to the threshold 31 is 0.5 m, the threshold is 0.1 m high and 0.15 m wide, and so on. As the position of the robot was recorded when the picture was taken, a plurality of these 2D representation can be transformed into 3D space and used to build a complete 3D map of the room as the robot moves and continuously records further sections of the room.



FIG. 5 illustrates a method according to a further embodiment of the present invention where the representation is created by means of. Steps S101-S103 are identical to those described with reference to FIG. 4. In an additional step S103b, the image data of the currently recorded picture is compared with image data of at least one previously recorded picture. This could be the directly preceding recorded picture, or an earlier recorded picture. Comparison can be made with even further earlier recorded pictures. Then, in step S103c, the line extracted from the currently recorded picture is adjusted on the basis of the comparison of the different sets of image data by using dead reckoning. Thus, by utilizing knowledge pertaining to previously known positions, a current position can be better estimated, and in case of disturbances (i.e. noise) in the picture, the noise can be filtered out since the noise is not likely to move across the picture in a way that is expected when comparing pictures with known relative movement in relation to each other.


Finally, in step S104′, a representation of the illuminated space along the projected laser lines is created from the adjusted extracted line, Thus, by means of comparing currently recorded image data with the representation made from previously recorded image data and applying dead reckoning, a more correct representation can be created, in respect of which the robot can be more accurately positioned.


Optionally, in addition to the extraction of the lines in the picture, the intensity and width of the lines are extracted. The information on the line-width and intensity can be used to filter out lines that are likely to be false. The fluctuation in intensity along a single line might be used as a debris indicator if the line has the position and inclination typical of a floor. Further, in practice, since the robot will tilt slightly back and forth and from side to side as it moves across the floor, image data that is used to generate a representation in the form of a 3D map may have to be adjusted, e.g. by assuming that that the floor on which the robot moves is flat and make a linear adjustment of the image data in the pictures. As a result, long lines that is near-horizontal in 3D space is adjusted to be perfectly horizontal, parameters of deviation for the near-horizontal lines are registered, and the remaining lines are adjusted with the corresponding parameters of deviation.


In case large amounts of data that represent points in 3D space are produced, they can be compressed to reduce the requirements on computation power of the processing unit of the robot positioning system according to embodiments of the present invention. For instance, a number of coherent points in space can be approximated by a line and only the start and stop points of the line are registered in memory and thus represent all the coherent points in space, and a number of coherent lines in space can be approximated by a surface.



FIG. 6 illustrates a further embodiment of the robot positioning system according to the present invention. When the robotic vacuum cleaner 20 encounters an obstacle, such as a carpet 25, causing it to slightly tilt the created representation may become incorrect, if it is assumed that robotic vacuum is parallel to the surface to be cleaned. This is even more evident in case the robotic vacuum cleaner 20 passes over a doorstep, in which case the robotic vacuum cleaner is capable of performing a tilting action in any direction to move its centre of gravity in order to easier climb over the doorstep. Thus, in this particular embodiment, the representation created is related to the surface across which the robotic vacuum cleaner moves. Hence the created representation is related to a coordinate system which is fixed to the floor and thus become invariant to robot tilt.


Even though the invention has been described with reference to specific exemplifying embodiments thereof, many different alterations, modifications and the like will become apparent for those skilled in the art. The described embodiments are therefore not intended to limit the scope of the invention, as defined by the appended claims.

Claims
  • 1. A method of positioning a robot comprising: illuminating a space with at least a first line laser projecting vertical laser beams within a field of view of a camera;recording, with the camera, a recorded picture of the space illuminated by the vertical laser beams;generating an extracted line by extracting, from the recorded picture, image data representing a line formed by the vertical laser beams being reflected against objects located within the space;comparing the image data of the extracted line of the recorded picture with image data of a previously extracted line of at least one previously recorded picture;generating an adjusted extracted line by adjusting the extracted line on the basis of the comparison by using dead reckoning; andcreating, from the adjusted extracted line, a representation of the illuminated space along the projected laser beams, and an estimate of a position of the robot in relation to the illuminated space.
  • 2. The method of claim 1, wherein: the step of illuminating a space further comprises illuminating the space with at least a second line laser projecting second vertical laser beams within the field of view of the camera;the step of generating an extracted line comprises extracting, from the recorded picture, image data representing respective lines formed by the respective vertical laser beams of the first and second line lasers being reflected against objects located within the space;the step of generating an adjusted extracted line comprises adjusting the respective lines on the basis of the comparison of the image data by using dead reckoning; andthe step of creating a representation from the adjusted extracted line comprises creating, from the extracted lines of the first and second line lasers, a representation of the illuminated space along the projected laser beams of the first and second line lasers.
  • 3. The method of claim 1, further comprising: acquiring a position estimate of the camera; andutilizing the position estimate to create the representation of the illuminated space, the representation being associated with coordinates on the basis of the position estimate.
  • 4. The method of claim 1, further comprising: rotating the camera around a vertical axis;repeatedly recording pictures from which the representation is created.
  • 5. The method of claim 2, further comprising: applying edge detection to the extracted image data in order to identify respective lines formed by the respective reflections of the respective beams of the first and second line lasers.
  • 6. The method of claim 1, further comprising: mapping the image data to unique sensor array coordinates of the camera; andassigning the unique coordinates to the extracted lines, wherein the representation is associated with the unique coordinates.
  • 7. A robot positioning system comprising: a camera;a processing unit; andat least a first line laser arranged to illuminate a space by projecting first vertical laser beams within a field of view of the camera; whereinthe camera is arranged to record a picture of the space illuminated by the first vertical laser beams; andthe processing unit is configured to extract, from the recorded picture, image data representing a first line formed by the first vertical laser beams being reflected against objects located within the space, compare the image data of the extracted first line of the recorded picture with image data of a previously extracted line of at least one previously recorded picture, adjust the image data representing the first line on the basis of the comparison by using dead reckoning, and create, from the image data representing the first line, a representation of the illuminated space along the projected first vertical laser beams and an estimation of a position of the robot in relation to the illuminated space.
  • 8. The robot positioning system of claim 7, further comprising: a second line laser arranged to illuminate the space within the field of view of the camera by projecting second vertical laser beams; whereinthe processing unit is arranged to extract, from the recorded picture, image data representing a respective lines formed by the first and second vertical laser beams and further to create, from the respective extracted lines, a representation of the illuminated space along the projected first and second vertical laser beams.
  • 9. The robot positioning system of claim 8, wherein the first and second line lasers are arranged on respective sides of the camera along an axis that is perpendicular to an optical axis of the camera.
  • 10. The robot positioning system of claim 9, wherein the first and second line lasers are arranged such that the first and second vertical laser beams intersect within the field of view of the camera.
  • 11. The robot positioning system of any one of claim 8, wherein the directions of the first and second vertical laser beams and the field of view of the camera are arranged such that a width (wC) of the illuminated space located within the field of view of the camera is greater than a width (wR) of the robot on which the robot positioning system is arranged.
  • 12. The robot positioning system of any one of claim 8, wherein the directions of the first and second vertical laser beams and the field of view of the camera are arranged such that a height (hC) of the illuminated space located within the field of view of the camera is greater than a height (hR) of the robot on which the robot positioning system is arranged.
  • 13. The robot positioning system of any one of claim 7, further comprising: an optical filter arranged at the camera, which optical filter is adapted to a wavelength of the light emitted by the first and second line laser.
  • 14. The robot positioning system of claim 7, wherein the camera and the first line laser are mounted on a robot and arranged to be rotatable around a vertical axis.
  • 15. The robot positioning system of claim 7, further comprising a positioning system for estimating an instantaneous position of the robot positioning system.
  • 16. The robot positioning system of claim 15, wherein the processing unit is further configured to: utilize the position estimate to create the representation of the illuminated space, the representation being associated with coordinates on the basis of the position estimate.
  • 17. The robot positioning system of claim 8, wherein the processing unit is further configured to: apply edge detection to the extracted image data in order to identify the respective lines formed by the reflections of the first and second vertical laser beams.
  • 18. The robot positioning system of claim 7, wherein the processing unit is further configured to: map the image data to unique sensor array coordinates of the camera; andassign the unique coordinates to the extracted lines, wherein the representation is associated with the unique coordinates.
  • 19. The robot positioning system of claim 8, further comprising: a dust sensor arranged to detect particles illuminated by the first and second line lasers by extracting image data indicating the illuminated particles, wherein operation of a robot on which robot positioning system is arranged is controlled in response to the detection of particles by the dust sensor.
  • 20. The robot positioning system of claim 7, wherein the processing unit is further configured to relate the created representation to a coordinate system which is fixed to a surface across which a robot associated with the robot positioning system moves.
Priority Claims (1)
Number Date Country Kind
1200514 Aug 2012 SE national
PCT Information
Filing Document Filing Date Country Kind
PCT/EP2013/067500 8/23/2013 WO 00
Publishing Document Publishing Date Country Kind
WO2014/033055 3/6/2014 WO A
US Referenced Citations (939)
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
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 Patzoid 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
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 Koriaragi 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 Maali Sep 1994 A
5353224 Lee Oct 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 Keil 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
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 Kawakami 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
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
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 Mori 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
7000623 Welsh Feb 2006 B2
7004269 Song Feb 2006 B2
7013200 Wakui Mar 2006 B2
7013527 Thomas, Sr. Mar 2006 B2
7015831 Karisson 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
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
7135992 Karlsson Nov 2006 B2
7143696 Ruclakevych Dec 2006 B2
7145478 Gonsalves Dec 2006 B2
7150068 Ragner Dec 2006 B1
7155308 Jones Dec 2006 B2
7155309 Peless Dec 2006 B2
7162338 Goricalves 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
7566839 Augenbraun Jun 2009 B2
7556108 Won Jul 2009 B2
7559269 Rudakevych Jul 2009 B2
7564571 Karabassi 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 Chiapbetta 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
7769490 Abramson Aug 2010 B2
7774158 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
7997113 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
8239992 Schnittman Aug 2012 B2
8244469 Jones Aug 2012 B2
8255092 Phillips Aug 2012 B2
8256542 Landry Aug 2012 B2
8265793 Cross Sep 2012 B2
8274406 Karlsson Sep 2012 B2
8281703 Moore Oct 2012 B2
8281731 Vosburgh Oct 2012 B2
8290619 McLunkin 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
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 Jonas 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 Vosburph 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
8461603 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 Karisson Aug 2013 B2
8515578 Chiappetta Aug 2013 B2
8516651 Jones Aug 2013 B2
8525995 Jones Sep 2013 B2
8526162 Tang Sep 2013 B2
8527113 Yamauchi Sep 2013 B2
8528157 Schnittman 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
8732895 Cunningham May 2014 B2
8743286 Hasegawa Jun 2014 B2
8745194 Uribe-Etxebarria Jun 2014 B2
8755936 Friedman Jun 2014 B2
8761931 Halloran Jun 2014 B2
8763200 Kim Jul 2014 B2
8774970 Knopow 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
8924042 Kim Dec 2014 B2
8961695 Romanov Feb 2015 B2
8985127 Konandreas Mar 2015 B2
9033079 Shin May 2015 B2
9037396 Pack May 2015 B2
9144361 Landry Sep 2015 B2
9360300 DiBernado Jun 2016 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 et al. 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 Aldred Apr 2005 A1
20050088643 Anderson Apr 2005 A1
20050156562 Cohen Jul 2005 A1
20050166354 Uehigashi 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
20060028306 Hukuba Feb 2006 A1
20060032013 Kim Feb 2006 A1
20060045981 Tsushi Mar 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 Tanaka Oct 2006 A1
20060236492 Sudo 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 JoeAugenbraun Mar 2007 A1
20070114975 Cohen 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
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
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 Lavarec 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
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 et al. 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
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
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
20110154589 Reindle Jun 2011 A1
20110181741 Jones 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 Fariow 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 Apr 2013 A1
20130103194 Jones Apr 2013 A1
20130105233 Couture May 2013 A1
20130117952 Schnittman May 2013 A1
20130118524 Konandreas 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 et al. 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
20130325178 Jones Dec 2013 A1
20130331987 Karlsson Dec 2013 A1
20130338525 Allen Dec 2013 A1
20130338828 Chiappetta Dec 2013 A1
20130338831 Noh 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
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 et al. Jan 2015 A1
20150039127 Matsumoto Feb 2015 A1
20150057800 Cohen Feb 2015 A1
20150197012 Schnittman Jul 2015 A1
20150206015 Ramalingam et al. Jul 2015 A1
20150265122 Han et al. Sep 2015 A1
20160306359 Lindhe Oct 2016 A1
Foreign Referenced Citations (129)
Number Date Country
2154758 Jun 1995 CA
1116818 Feb 1996 CN
103027634 Apr 2013 CN
3536907 Apr 1986 DE
9307500 Jul 1993 DE
4211789 Oct 1993 DE
4340367 Jun 1995 DE
19849978 May 2000 DE
102010000174 Jul 2011 DE
102010000573 Sep 2011 DE
102010037672 Mar 2012 DE
0142594 May 1985 EP
0358628 Mar 1990 EP
0474542 Mar 1992 EP
0569984 Nov 1993 EP
0606173 Jul 1994 EP
1099143 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
2561787 Feb 2013 EP
2578125 Apr 2013 EP
2583609 Apr 2013 EP
2604163 Jun 2013 EP
2447800 Apr 2014 EP
2741483 Jun 2014 EP
2772815 Sep 2014 EP
2999416 Jun 2014 FR
2355523 Apr 2001 GB
2382251 May 2003 GB
249446 Mar 2013 GB
1447943 Oct 2013 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
03166074 Jul 1991 JP
04260905 Sep 1992 JP
0584200 Apr 1993 JP
0584210 Apr 1993 JP
05084200 Apr 1993 JP
05224745 Apr 1993 JP
05189041 Jul 1993 JP
05228090 Sep 1993 JP
064133 Jan 1994 JP
0683442 Mar 1994 JP
06125861 May 1994 JP
06144215 May 1994 JP
06179145 Jun 1994 JP
075922 Jan 1995 JP
0759695 Mar 1995 JP
07129239 May 1995 JP
07281742 Oct 1995 JP
08326025 Dec 1995 JP
08089455 Apr 1996 JP
0944240 Feb 1997 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
2002355204 Dec 2002 JP
2002366228 Dec 2002 JP
2003280740 Oct 2003 JP
2004166968 Jun 2004 JP
2004198212 Jul 2004 JP
2004303134 Oct 2004 JP
2005040597 Feb 2005 JP
2005124753 May 2005 JP
2005141636 Jun 2005 JP
2006087507 Apr 2006 JP
2006185438 Jul 2006 JP
2006231477 Sep 2006 JP
2006314669 Nov 2006 JP
2007143645 Jun 2007 JP
2007213236 Aug 2007 JP
2007226322 Sep 2007 JP
2007272665 Oct 2007 JP
2008146617 Jun 2008 JP
2008290184 Dec 2008 JP
2009509220 Mar 2009 JP
2009193240 Aug 2009 JP
2010507169 Mar 2010 JP
2010079869 Apr 2010 JP
2010526594 Aug 2010 JP
2011045694 Mar 2011 JP
2011253361 Dec 2011 JP
2012216051 Nov 2012 JP
2013089256 May 2013 JP
2004009253 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
03022120 Mar 2003 WO
03024292 Mar 2003 WO
03026474 Apr 2003 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
2015016580 Feb 2015 WO
Non-Patent Literature Citations (90)
Entry
Written Opinion for International Application No. PCT/EP2013/067500 mailed Dec. 10, 2013.
International Search Report for International Application No. PCT/EP2013/067500 mailed Dec. 10, 2013.
Michael Carsten Bosse, “Atlas: A Framework for Large Scale Automated Mapping and Localization”, Massachusetts Institute of Technology, Feb. 2004, Part 1, 140 pages.
Michael Carsten Bosse, “Atlas: A Framework for Large Scale Automated Mapping and Localization”, Massachusetts Institute of Technology, Feb. 2004, Part 2, 67 paces.
“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, an 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
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 Fionda, AAAI 1993 Fail 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.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, Ltd., 1995, Chapters, 4 and 5.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, Ltd., 1995, Chapters 6, 7 and 10.
Everett, Sensors for Mobile Robots Theory and Application, A.K. Peters, Ltd., 1995, Chapters 15 and 16.
Everett, et al, “Survey of Collision Avoidance and Ranging Sensors for Mobile Robots”, Revision 1, Technical Report 1194, Dec. 1992, pp. 1-154.
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 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 Search 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 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/EP32013/077657, dated Aug. 18, 2014, 10 pages.
International Search Report for International Application No. PCT/EP2013/057814 dated Dec. 20, 2013.
International Search Report for International Application No. PCT/EP2013/057815 dated Apr. 2, 2014.
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 6 and 9.
Jones et al. Mobile Robots Inspiration to Implementation, Second Edition, A.K. Peters, Ltd., 1999, Chapters 1 and 5.
Jones et al., Mobile Robots Inspiration to Implementation, Second Edition, A.K. Peters, Ltd., 1999, Chapters 10 and 11.
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, et al. “Sensor-based navigation of a mobile robot in an indoor environment”, Robotics and Autonomous Systems, 2002, Elsevier.
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/ 95 25, Cover page + pp. 1-14.
Yamamoto. “SOZZY: A Hormone-Driven Autonomous Vacuum Cleaner”, From: AAAI Technical Report F3-93-03, Matasushda Research Institute, Tokyo, and MIT Artificial Intelligence laboratory, Massachusetts, pp. 116-124 + Figure 9 and Figure 11.
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/EP2014/069074, dated May 11, 2015, 9 pages.
Non Final Office Action for U.S. Appl. No. 15/101,257, dated Feb. 10, 2017, 10 pages.
Extended European Search Report for European Application No. 16176479.0, dated Nov. 11, 2016, 9 pages.
Non Final Office Action for U.S. Appl. No. 15/101,235 dated Apr. 21, 2017, 10 pages.
Final Office Action for U.S. Appl. No. 15/100,667, dated Apr. 21, 2017, 26 pages.
Non Final Office Action for U.S. Appl. No. 15/100,667, dated Sep. 12, 2016, 24 pages.
International Search Report and Writtent Opinion of the International Searching Authority for International Application No. PCT/EP2014/078144, 7 pages.
Japanese Office Action for Japanese Application No. 2016-506795, dated Feb. 7, 2017 with translation, 6 pages.
Chinese Office Action for Chinese Application No. 20130075510.9, dated Feb. 6, 2017 with translation, 14 pages.
Japanese Office Action for Japanese Application No. 2016-506794, dated Feb. 7, 2017 with translation, 10 pages.
Chinese Office Action for Chinese Application No. 201380075503.9, dated Febraury 13, 2017 with translation, 18 pages.
Interational 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, 19 pages.
International Search Report and Written Opinion of the International Searching Authority for Internatonal Applicaion No. PCT/EP2014/0077142, dated Sep. 11, 2015, 8 pages.
Chung et al., “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.
Non Final Office Action for U.S. Appl. No. 15/101,212, dated May 17, 2017, 8 pages.
Japanese Office Action forApplication for Japanese Application No. 2015-528969, dated Apr. 7, 2017 with translation, 4 pages.
Notice of Allowance for U.S. Appl. No. 15/101,257, dated Jul. 6, 2017, 9 pages.
Non Final Office Action for U.S. Appl. No. 15/102,015, dated Aug. 17, 2017, 13 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.
Japanese Office Action for Application for Japanese Application No. 2015-528969, dated Apr. 7, 2017 with translation, 4 pages.
Notice of Reasons for Rejection for Japanese Application No. 2016-526764, dated Aug. 25, 2017 with translation, 6 paes.
Notification fo Reasons for Rejection for Japanese Application No. 2016-526765, dated Aug. 25, 2017 with translation, 7 pages.
Notifcation 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.
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.
Notification of Reasons for Rejection for Japanese Application No. 2016-526947, dated Sep. 21, 2017 with translation, 8 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.
Notice of Allowance for U.S. Appl. No. 15/102,015, dated Dec. 11, 2017, 8 pages.
Related Publications (1)
Number Date Country
20150185322 A1 Jul 2015 US