Method and System for Controlling a Remote Vehicle

• US 20100066587A1
• Filed: 09/15/2009
• Published: 03/18/2010
• Est. Priority Date: 07/14/2006
• Status: Abandoned Application

• Current Assignee: iRobot Corporation
• Original Assignee: iRobot Corporation
• Inventors: Yamauchi, Brian Masao, Jones, Christopher Vernon, Lenser, Scott Raymond
• Application Number:
  US12/560,410
• Publication Number:
  US 20100066587A1
• Time in Patent Office: Days
• US Class Current: 342/70
• CPC Class Codes: G01S 13/0209 Systems with very large relative bandwidth, i.e. larger than 10 %, e.g. baseband, pulse, carrier-free, ultrawideband
• CPC Class Codes: G01S 13/865 Combination of radar systems with lidar systems
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/881 for robotics
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 7/003 Transmission of data between radar, sonar or lidar systems and remote stations
• CPC Class Codes: G01S 7/414 Discriminating targets with respect to background clutter
• 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 1/024 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 1/0255 using acoustic signals, e.g. ultra-sonic singals sonar systems designed for anti-collision purposes G01S15/93
• CPC Class Codes: G05D 1/0257 using a radar radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931
• 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: G05D 1/0278 using satellite positioning signals, e.g. GPS

Abstract

A system for controlling a remote vehicle comprises: a LIDAR sensor, a stereo vision camera, and a UWB radar sensor; a sensory processor configured to process data from one or more of the LIDAR sensor, the stereo vision camera, and the UWB radar sensor; and a remote vehicle primary processor configured to receive data from the sensory processor and utilize the data to perform an obstacle avoidance behavior.

Claims

1. A system for controlling a remote vehicle, the system comprising:

a LIDAR sensor, a stereo vision camera, and a UWB radar sensor;

a sensory processor configured to process data from one or more of the LIDAR sensor, the stereo vision camera, and the UWB radar sensor; and

a remote vehicle primary processor configured to receive data from the sensory processor and utilize the data to perform an obstacle avoidance behavior.

2. The system of claim 1, further comprising a UWB radar processor configured to process data from the UWB radar sensor.

3. The system of claim 2, wherein the UWB radar processor sends data from the UWB radar sensor to the sensory processor.

4. The system of claim 2, wherein the UWB radar processor sends data from the UWB radar sensor to the remote vehicle primary processor.

5. The system of claim 1, further comprising a GPS and an IMU, the sensory processor being configured to receive data from the GPS and the IMU.

6. The system of claim 1, wherein data from the LIDAR sensor and the UWB radar sensor is integrated and utilized by the remote vehicle process to perform an obstacle avoidance behavior.

7. The system of claim 6, wherein the integrated LIDAR sensor and UWB radar sensor data is stored in an occupancy grid map.

8. The system of claim 1, wherein local perceptual space stores a representation of obstacles in the immediate vicinity of the remote vehicle via data from the LIDAR sensor and the UWB radar sensor.

9. A system for allowing a remote vehicle to discern solid impassable objects from rain, snow, fog, and smoke for the purposes of performing an obstacle avoidance behavior, the system comprising:

a LIDAR sensor, a stereo vision camera, a UWB radar sensor, and a GPS;

a sensory processor configured to process data from one or more of the LIDAR sensor, the stereo vision camera, the UWB radar sensor, and the GPS; and

a remote vehicle primary processor configured to receive data from the sensory processor and utilize the data to perform the obstacle avoidance behavior,

wherein data from the UWB radar sensor is integrated with data from the LIDAR sensor to yield data for the obstacle avoidance behavior that represents solid impassable objects rather than rain, snow, fog, and smoke.

10. The system of claim 9, further comprising a UWB radar processor configured to process data from the UWB radar sensor.

11. The system of claim 10, wherein the UWB radar processor sends data from the UWB radar sensor to the sensory processor.

13. The system of claim 10, wherein the UWB radar processor sends data from the UWB radar sensor to the remote vehicle primary processor.

14. The system of claim 9, wherein the integrated LIDAR sensor and UWB radar sensor data is stored in an occupancy grid map.

15. The system of claim 9, wherein local perceptual space stores a representation of impassable obstacles in the immediate vicinity of the remote vehicle via data from the LIDAR sensor and the UWB radar sensor.

16. A method for allowing a remote vehicle to discern solid impassable objects from rain, snow, fog, and smoke for the purposes of performing an obstacle avoidance behavior, the method comprising:

integrating data from a LIDAR sensor with data from a UWB radar sensor to yield data for the obstacle avoidance behavior that represents solid impassable objects rather than rain, snow, fog, and smoke.

17. The method of claim 16, further comprising filtering the data from the UWB radar sensor to remove ground clutter.

18. The method of claim 16, further comprising storing the integrated data in an occupancy grid map.

19. The method of claim 16, further comprising storing a representation of the integrated data in local perceptual space.

20. The method of claim 16, further comprising using data from the UWB radar sensor to provide data regarding objects that are not detectable via LIDAR data or stereo vision data.