Autonomous Mobile Robot

• US 20110208357A1
• Filed: 12/17/2010
• Published: 08/25/2011
• Est. Priority Date: 12/30/2005
• Status: Abandoned Application

• Current Assignee: iRobot Corporation
• Original Assignee: iRobot Corporation
• Inventors: Yamauchi, Brian
• Application Number:
  US12/971,438
• Publication Number:
  US 20110208357A1
• Time in Patent Office: Days
• US Class Current: 700/258
• CPC Class Codes: G05D 1/0038 by providing the operator with simple or augmented images from one or more cameras located onboard the vehicle, e.g. tele-operation images analyzed by a computer and used for automatic navigation G05D1/0246
• CPC Class Codes: G05D 1/0044 by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps maps used for automatic navigation G05D1/0274; flight directors G01C23/005
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0251 extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision stereoscopic image analysis H04N13/00; depth recovery from images G06T7/593
• CPC Class Codes: G05D 1/027 comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• CPC Class Codes: G05D 1/0278 using satellite positioning signals, e.g. GPS

Abstract

A mobile robot is equipped with a range finder and a stereo vision system. The mobile robot is capable of autonomously navigating through urban terrain, generating a map based on data from the range finder and transmitting the map to the operator, as part of several reconnaissance operations selectable by the operator. The mobile robot employs a Hough transform technique to identify linear features in its environment, and then aligns itself with the identified linear features in order to navigate through the urban terrain; while at the same time, a scaled vector field histogram technique is applied to the combination of range finder and stereo vision data to detect and avoid obstacles the mobile robot encounters when navigating autonomously. Also, the missions performed by the mobile robot may include limitation parameters based on distance or time elapsed, to ensure completion of the autonomous operations.

Claims

1-20. -20. (canceled)

21. A mobile robot, comprising:

a drive system configured to propel the mobile robot across terrain;

a range sensor configured to detect a distance between the mobile robot and a physical object in an environment of the mobile robot; and

a processor communicatively connected to the range sensor and to the drive system, and configured to execute;

a mapping routine configured to maintain an occupancy grid map corresponding to linear features of one or more physical objects in the environment of the mobile robot of the environment of the mobile robot, a linear feature routine configured to track votes for line hypotheses to detect one or more linear patterns in the occupancy grid map and to determine a strongest line among the one or more linear patterns, and a navigational routine configured to control the drive system to move the mobile robot in a direction aligned in parallel with the linear feature of a first physical object corresponding to the strongest line among the one or more linear patterns;

wherein the strongest line includes the line hypothesis corresponding to a linear feature of the first physical object in the environment of the mobile robot and having a greatest number of votes among the line hypotheses that have at least a threshold number of votes.

22. The mobile robot according to claim 21, further comprising a position reckoner configured to determine a location of the mobile robot.

23. The mobile robot according to claim 21, further comprising a teleoperation transceiver configured to receive a command from a teleoperation console and/or to transmit map data to the teleoperation console.

24. The mobile robot according to claim 22, wherein the processor is further configured to execute a localization routine configured to update the occupancy grid map using a scaled vector field histogram based on input from the range sensor and the position reckoner.

25. The mobile robot according to claim 21, wherein the processor is further configured to designate a location of the mobile robot when the mapping routine begins maintaining the occupancy grid map as an initial location, and

wherein the navigational routine is further configured to prevent the drive system from moving the mobile robot farther than a leash distance from the initial location.

26. The mobile robot according to claim 23, wherein the processor is further configured to execute a perimeter-following routine configured to cause the mobile robot to circumnavigate a reconnaissance target identified using a Hough transform, to record the occupancy grid map when circumnavigating the reconnaissance target, and to transmit the recorded occupancy grid map to the teleoperation console.

27. The mobile robot according to claim 23, wherein the processor is further configured to execute a street-following routine configured to cause the mobile robot to navigate to a first location selected by the operator, to identify a street using a scaled vector field histogram, to traverse the identified street to a specified distance from the initial location, to record the occupancy grid map when traversing the identified street, to return to the first location, and to transmit the recorded occupancy grid map to the teleoperation console.

28. The mobile robot according to claim 25, further comprising an operator interface configured to cause the mobile robot to perform a robot mission starting from the initial location of the mobile robot when the operator interface is operated.

29. The mobile robot according to claim 23, wherein the processor is further configured to execute a rallying routine when communication with the teleoperation console fails.

30. The mobile robot according to claim 29, wherein the rallying routine is configured to cause the mobile robot to move toward a predetermined location until communication is established with the teleoperation console.

31. The mobile robot according to claim 29, wherein the rallying routine is configured to cause the mobile robot to reverse its heading until communication is established with the teleoperation console.

32. A method for controlling a mobile robot, comprising:

detecting a distance between the mobile robot and a physical object in an environment of the mobile robot;

maintaining an occupancy grid map of the environment of the mobile robot,

detecting one or more linear patterns in the occupancy grid map corresponding to linear features of one or more physical objects in the environment of the mobile robot;

determining a strongest line among the one or more linear patterns; and

navigating the mobile robot in a direction aligned in parallel with the linear feature of a first physical object corresponding to the strongest line;

wherein determining the strongest line comprises executing a linear feature routine comprising tracking votes for line hypotheses to detect the one or more linear patterns in the occupancy grid map; and

wherein the strongest line includes the line hypothesis corresponding to a linear feature of the first physical object in the environment of the mobile robot and having a greatest number of votes among the line hypotheses that have at least a threshold number of votes.

33. The method according to claim 32, further comprising:

reckoning a position of the mobile robot using a global positioning satellite receiver, an odometer, or an inertial navigation system; and

updating the occupancy grid map using a scaled vector field histogram based on the reckoned position of the mobile robot and the detected distance between the mobile robot and the object in the environment of the mobile robot.

34. The method according to claim 33, further comprising preventing the mobile robot from navigating farther than a leash distance from an initial location.

35. The method according to claim 32, further comprising receiving a command from a teleoperation console.

36. The method according to claim 32, further comprising:

identifying a reconnaissance target using a Hough transform;

navigating the mobile robot to circumnavigate the reconnaissance target;

recording the occupancy grid map when circumnavigating the reconnaissance target; and

transmitting the recorded occupancy grid map to a teleoperation console.

37. The method according to claim 32, further comprising:

navigating the mobile robot to a first location selected by an operator;

identifying a street using a scaled vector field histogram;

traversing the street to a specified distance from an initial location;

recording the occupancy grid map when traversing the street;

returning to the first location; and

transmitting the recorded occupancy grid map to a teleoperation console.

38. The method according to claim 32, further comprising navigating the mobile robot toward a predetermined location or in a reverse heading until communication is established with a teleoperation console when communication with the teleoperation console fails.

39. The method according to claim 32, wherein the mobile robot includes a drive system for propelling the mobile robot across terrain, a range sensor for detecting the distance between the mobile robot and the object in the environment of the mobile robot, and a processor communicatively connected to the range sensor and to the drive system for executing:

a mapping routine for maintaining the occupancy grid map of the environment of the mobile robot, a linear feature routine for detecting the one or more linear patterns in the occupancy grid map and determining the strongest line among the one or more linear patterns, and a navigational routine for controlling the drive system to move the mobile robot in a direction aligned with the strongest line among the one or more linear patterns,

wherein the detecting the distance between the mobile robot and the object in the environment of the mobile robot is performed by the range sensor of the mobile robot, and

wherein the maintaining the occupancy grid map of the environment of the mobile robot, the detecting the one or more linear patterns in the occupancy grid map, the determining the strongest line among the one or more linear patterns, and the navigating the mobile robot in the direction aligned with the strongest line are performed by the processor of the mobile robot.