Mobile robot system

• US 9,014,848 B2
• Filed: 02/22/2011
• Issued: 04/21/2015
• Est. Priority Date: 05/20/2010
• Status: Active Grant

• Current Assignee: iRobot Corporation
• Original Assignee: iRobot Corporation
• Inventors: Farlow, Timothy S., Rosenstein, Michael, Halloran, Michael, Won, Chikyung, Shamlian, Steven V., Chiappetta, Mark
• Primary Examiner(s): Tran, Khoi
• Assistant Examiner(s): MOYER, DALE S
• Application Number:
  US13/032,406
• Publication Number:
  US 20110288684A1
• Time in Patent Office: 1,519 Days
• Field of Search: 318/568.12, 700245-264, 701/23, 701/25, 701/532, 901/1, 901/47
• US Class Current: 700/245
• CPC Class Codes: B25J 11/009 Nursing, e.g. carrying sick persons, pushing wheelchairs, distributing drugs
• CPC Class Codes: B25J 19/023 including video camera means
• CPC Class Codes: B25J 5/007 mounted on wheels
• CPC Class Codes: B25J 9/1697 Vision controlled systems
• CPC Class Codes: G05D 1/0011 associated with a remote control arrangement
• CPC Class Codes: G05D 1/0022 characterised by the communication link data switching networks in general H04L12/00
• 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 1/0227 using mechanical sensing means, e.g. for sensing treated area
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0242 using non-visible light signals, e.g. IR or UV signals
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0255 using acoustic signals, e.g. ultra-sonic singals sonar systems designed for anti-collision purposes G01S15/93
• 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 1/0272 comprising means for registering the travel distance, e.g. revolutions of wheels measuring distance traversed on the ground by vehicles, e.g. using odometers G01C22/00
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: H04N 7/142 Constructional details of the terminal equipment, e.g. arrangements of the camera and the display
• CPC Class Codes: H04N 7/144 camera and display on the same optical axis, e.g. optically multiplexing the camera and display for eye to eye contact
• CPC Class Codes: Y10S 901/01 Mobile robot
• CPC Class Codes: Y10S 901/47 Optical

Abstract

A robot system includes a mobile robot having a controller executing a control system for controlling operation of the robot, a cloud computing service in communication with the controller of the robot, and a remote computing device in communication with the cloud computing service. The remote computing device communicates with the robot through the cloud computing service.

Claims

1. A method of operating a mobile robot, the method comprising:

receiving, at a data processing device, a layout map corresponding to an environment of the robot;

moving the robot in the environment to one or more layout map locations on the layout map;

recording, in non-transitory memory in communication with the data processing device, one or more robot map locations on a robot map, the robot map corresponding to the environment and produced by the robot;

determining, using the data processing device, a distortion between the robot map and the layout map using the recorded robot map locations of the robot map and the corresponding layout map locations of the layout map; and

applying, using the data processing device, the determined distortion to a target layout map location to determine a corresponding target robot map location.

2. The method of claim 1, further comprising receiving, at the data processing device, the layout map from a cloud computing service.

3. The method of claim 2, further comprising producing the layout map on an application executing on a remote computing device and storing the layout map on a remote cloud storage device using the cloud computing service.

4. The method of claim 1, further comprising:

determining, using the data processing device, a scaling size, origin mapping, and rotation between the layout map and the robot map using existing layout map locations and recorded robot map locations; and

resolving, using the data processing device, a robot map location corresponding to the target layout map location.

5. The method of claim 4, further comprising applying data processing device, an affine transformation to the determined scaling size, origin mapping, and rotation to resolve the target robot map location.

6. The method of claim 1, further comprising determining, using the data processing device, a triangulation between layout map locations that bound the target layout map location.

7. The method of claim 6, further comprising determining, using the data processing device, a scale, rotation, translation, and skew between a triangle mapped in the layout map and a corresponding triangle mapped in the robot map and applying the determined scale, rotation, translation, and skew to the target layout map location to determine the corresponding robot map point.

8. The method of claim 1, further comprising:

determining, using the data processing device, distances between all layout map locations and the target layout map location;

determining, using the data processing device, a centroid of the layout map locations;

determining, using the data processing device, a centroid of all recorded robot map locations; and

for each layout map location, determining a rotation and a length scaling to transform a vector running from the layout map centroid to the target layout location into a vector running from the robot map centroid to the target robot map location.

9. The method of claim 1, further comprising producing the robot map using a sensor system of the robot.

10. The method of claim 9, further comprising

emitting light onto a scene of the environment;

receiving reflections of the emitted light off surfaces of the scene;

determining, using the data a distance of each reflecting surface; and

constructing, using the data processing device, a three-dimensional depth map of the scene.

11. The method of claim 10, further comprising emitting a speckle pattern of light onto the scene and receiving reflections of the speckle pattern from the scene.

12. The method of claim 11, further comprising storing, in the non-transitory memory, reference images of the speckle pattern as reflected off a reference object in the scene, the reference images captured at different distances from the reference object.

13. The method of claim 12, further comprising capturing at least one target image of the speckle pattern as reflected off a target object in the scene and comparing the at least one target image with the reference images for determining a distance of the reflecting surfaces of the target object.

14. The method of claim 13, further comprising determining a primary speckle pattern on the target object and computing at least one of a respective cross-correlation and a decorrelation between the primary speckle pattern and the speckle patterns of the reference images.

15. The method of claim 13, further comprising maneuvering the robot with respect to the target object based on the determined distances of the reflecting surfaces of the target object.

16. The method of claim 10, further comprising determining, using the data processing device, a time-of-flight between emitting the light and receiving the reflected light and determining, using the data processing device, a distance to the reflecting surfaces of the scene.

17. The method of claim 10, further comprising emitting the light onto the scene in intermittent pulses.

18. The method of claim 17, further comprising altering a frequency of the emitted light pulses.