HIGH INTEGRITY PERCEPTION FOR MACHINE LOCALIZATION AND SAFEGUARDING

• US 20100063651A1
• Filed: 09/11/2008
• Published: 03/11/2010
• Est. Priority Date: 09/11/2008
• Status: Active Grant

• Current Assignee: Deere & Company
• Original Assignee: Deere & Company
• Inventors: Anderson, Noel Wayne
• Granted Patent: US 8,818,567 B2
• Time in Patent Office: Days
• US Class Current: 701/2
• 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 1/0242 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 1/0257 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 1/0261 using magnetic plots
• 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
• CPC Class Codes: G05D 2201/0201 Agriculture or harvesting machine

Abstract

The illustrative embodiments provide a method for processing sensor data and controlling the movement of a vehicle. An operating environment around the vehicle is identified and sensor data is selected from a set of sensors. A dynamic condition is identified using a plurality of different types of sensors on the vehicle. In response to the dynamic condition being identified, the movement of the vehicle is controlled. Sensor data for a plurality of vehicles is managed by receiving sensor data at the plurality of vehicles, each with a plurality of sensors. In response to a selected vehicle within the plurality of vehicles being unable to obtain needed sensor data, collected sensor data from a number of other vehicles in the plurality of vehicles can be obtained to form alternate sensor data used to control the vehicle.

Claims

1. A method for processing sensor data for a vehicle, the method comprising:

identifying an environment around the vehicle to form an operating environment; and

selecting sensor data from a set of sensors within a plurality of redundant sensors based on the operating environment.

2. The method of claim 1, wherein the selecting step comprises:

activating the set of sensors within the plurality of redundant sensors based on the operating environment to select the sensor data from the set of sensors within the plurality of redundant sensors.

3. The method of claim 1, wherein the identifying step comprises:

obtaining the environment around the vehicle from a knowledge base.

4. The method of claim 1, wherein the sensor data is selected sensor data and further comprising:

performing localization using the selected sensor data.

5. The method of claim 1, wherein the sensor data is selected sensor data and further comprising:

performing obstacle detection using the selected sensor data.

6. The method of claim 1, wherein the sensor data is selected sensor data and further comprising:

controlling movement of the vehicle using the selected sensor data.

7. The method of claim 1, wherein the plurality of redundant sensors provide a set of fields of regard for the vehicle.

8. A method for controlling a vehicle, the method comprising:

identifying a dynamic condition using a plurality of different types of sensors on the vehicle, wherein some types of sensors are more accurate that other types of sensors within the plurality of different types of sensors in a particular environment; and

responsive to identifying the dynamic condition, controlling movement of the vehicle based on the dynamic condition.

9. The method of claim 8, wherein the plurality of different types of sensors is a plurality of redundant sensors.

10. The method of claim 8, wherein the identifying step comprises:

receiving data from the plurality of different types of sensors on the vehicle to form received data; and

generating a thematic map using the received data and a knowledge base.

11. The method of claim 10, wherein the generating step comprises:

identifying the location of the vehicle;

identifying a map based on the location of the vehicle; and

placing thematic features into the map using the received data and the knowledge base.

12. The method of claim 11, wherein the controlling step comprises:

moving the vehicle using the thematic map.

13. The method of claim 10, wherein the knowledge base further comprises an online knowledge base, an a priori knowledge base, and a learned knowledge base.

14. The method of claim 13, wherein the identifying step further comprises:

receiving sensor data from the plurality of different types of sensors on the vehicle; and

applying weights to the sensor data using the online knowledge base to form weighted sensor data.

15. The method of claim 13, wherein the online knowledge base is located at a remote location and accessible to control the vehicle.

16. The method of claim 14, further comprising:

selecting a portion of the weighted sensor data to form selected sensor data; and

performing localization using the selected sensor data.

17. The method of claim 16, wherein the step of performing localization using the selected sensor data comprises:

identifying a set of objects in an environment around the vehicle using the selected sensor data; and

identifying a location of the vehicle using the location of the set of objects.

18. The method of claim 17, wherein the step of identifying the set of objects in the environment around the vehicle using the selected sensor data comprises:

identifying the set of objects using the sensor data and the knowledge base.

19. The method of claim 17, wherein the knowledge base specifies the set of objects based on the environment.

20. The method of claim 10, wherein the step of identifying the dynamic condition comprises:

identifying a set of differences between an environment as detected by the plurality of sensors for the vehicle and a description of the environment in the knowledge base.

21. The method of claim 20, wherein the set of differences comprises at least one of a change in an object in the environment, a new object in the environment, and a missing object from the environment.

22. The method of claim 8, wherein the plurality of different types of sensors comprises at least one of a global positioning system, structured light sensor, two dimensional/three dimensional lidar, dead reckoning, infrared camera, visible light camera, radar, ultrasonic sonar, and radio frequency identification reader.

23. The method of claim 8, further comprising:

monitoring the plurality of different types of sensors for sensor integrity.

24. The method of claim 23, further comprising:

identifying a fault in at least one sensor in the plurality of different types of sensors.

25. The method of claim 24, wherein the fault in at least one sensor is sensor degradation.

26. The method of claim 24, wherein the fault in at least one sensor is sensor failure.

27. The method of claim 24, further comprising:

responsive to identifying a fault in at least one sensor in the plurality of different types of sensors, generating an alert displaying the fault in at least one sensor in the plurality of different types of sensors.

28. The method of claim 24, further comprising:

responsive to identifying the fault in at least one sensor in the plurality of different types of sensors, selecting a different sensor to compensate for the fault in at least one sensor.

29. The method of claim 24, further comprising:

responsive to identifying the fault in at least one sensor in the plurality of different types of sensors, transmitting a request for sensor data to a sensor system of another vehicle.

30. The method of claim 29, further comprising:

receiving the sensor data from the sensor system of another vehicle; and

performing localization based on the sensor data from the sensor system of another vehicle.

31. A method for controlling a vehicle, the method comprising:

identifying an environment using a plurality of sensors on the vehicle, wherein the plurality of sensors comprises at least one of a global positioning system, structured light sensor, two dimensional/three dimensional lidar, dead reckoning, far and medium infrared camera, visible light camera, radar, ultrasonic sonar, and radio frequency identification reader;

identifying the location of the vehicle;

identifying a map based on the location of the vehicle;

identifying a set of objects in the environment using data received from the plurality of sensors and a knowledge base, wherein the knowledge base specifies the set of objects based on the environment;

placing thematic features into the map using the set of objects identified and the map identified;

controlling the vehicle using the knowledge base, wherein the knowledge base further comprises an online knowledge base, an a priori knowledge base, and a learned knowledge base;

monitoring the plurality of sensors for sensor integrity;

identifying a fault in at least one sensor in the plurality of sensors, wherein the fault in at least one sensor is one of sensor degradation and sensor failure;

responsive to identifying the fault in at least one sensor in the plurality of sensors, generating an alert displaying the fault in at least one sensor in the plurality of sensors;

responsive to identifying the fault in at least one sensor in the plurality of sensors, selecting a different sensor to compensate for the fault in at least one sensor;

responsive to identifying the fault in at least one sensor in the plurality of sensors, transmitting a request for sensor data to a sensor system of another vehicle;

receiving the sensor data from the sensor system of another vehicle; and

performing localization based on the sensor data from the sensor system of another vehicle.