SYSTEM AND METHOD FOR GOVERNING A SPEED OF AN AUTONOMOUS VEHICLE

• US 20120083982A1
• Filed: 10/05/2010
• Published: 04/05/2012
• Est. Priority Date: 10/05/2010
• Status: Active Grant

• Current Assignee: Deere & Company
• Original Assignee: Deere & Company
• Inventors: Bonefas, Zachary Thomas, Anderson, Noel Wayne
• Granted Patent: US 9,043,129 B2
• Time in Patent Office: Days
• US Class Current: 701/70
• CPC Class Codes: G05D 1/0223 involving speed control of the vehicle vehicle fittings for automatically controlling, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator B60K31/00
• 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 1/0257 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 1/0274 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 method of adjusting a speed of a mobile machine is provided. Image data of a location is collected where currently generated sensor data and previously generated sensor data indicate a discontinuity in sensor data. The image data is analyzed to determine if a non-motion blur score for the image data is above a threshold value. Then, a speed of the mobile machine is adjusted based on a determination that the non-motion blur score is above the threshold value.

Claims

1. A method of adjusting a speed of a mobile machine, the method comprising:

collecting image data of a location where currently generated sensor data and previously generated sensor data indicate a discontinuity in sensor data;

analyzing the image data to determine if a non-motion blur score for the image data is above a threshold value; and

adjusting, by a machine controller, a speed of the mobile machine based on a determination that the non-motion blur score is above the threshold value.

2. The method of claim 1 further comprising:

determining, by the machine controller, the location within an operating environment of the mobile machine where the discontinuity exists between the currently generated data and the previously generated data for the operating environment;

selecting, by the machine controller, the image data that corresponds to the location where the discontinuity exists between the currently generated data and the previously generated data for the operating environment;

determining, by the machine controller, whether the non-motion blur score for the selected image data is above the threshold value;

responsive to a determination that the non-motion blur score for the selected image data is above the threshold level, determining, by the machine controller, that the operating environment includes an obscurant; and

adjusting, by the machine controller, the speed of the mobile machine based on an optical density of the obscurant in the operating environment.

3. The method of claim 1 further comprising:

responsive to a determination that the non-motion blur score for the image data is not above the threshold value, determining, by the machine controller, that an operating environment of the mobile machine includes an obstacle;

determining, by the machine controller, a type of the obstacle and a distance to the obstacle using a sensor system and a knowledge base associated with the mobile machine; and

initiating, by the machine controller, an action for the mobile machine based on the type of and the distance to the obstacle.

4. The method of claim 1 further comprising:

emitting, by a sensor associated with the mobile machine, pulses into an operating environment around the mobile machine;

receiving, by the sensor, reflections of the pulses from objects in the operating environment;

generating, by the machine controller, current data for the operating environment based on the reflections of the pulses;

comparing, by the machine controller, the current data with the previously generated data for the operating environment; and

determining, by the machine controller, whether continuity exists between the current data and the previously generated data.

5. The method of claim 2 wherein the obscurant is at least one of dust, fog, smoke, snow, rain, ash, or steam within the operating environment.

6. The method of claim 1 wherein the image data that corresponds to the location where the discontinuity exists between the currently generated data and the previously generated data is captured by an imaging device, and wherein the imaging device is a video camera.

7. The method of claim 1 wherein the machine controller adjusts the speed of the mobile machine by decreasing a maximum allowed speed of the mobile machine.

8. The method of claim 3 wherein the action is an avoidance maneuver.

9. The method of claim 1 wherein the mobile machine is one of a plurality of mobile machines performing tasks within an operating environment, and wherein the plurality of mobile machines are in communication with each other via a network.

10. The method of claim 1 wherein the mobile machine is an autonomous mobile robotic machine.

11. The method of claim 1 wherein the machine controller is located on the mobile device.

12. The method of claim 1 wherein the machine controller is located on a remote server device.

13. A mobile machine comprising:

a propulsion system;

a steering system;

a sensor system for collecting data regarding an operating environment of the mobile machine; and

a machine controller coupled to the propulsion system, the steering system, and the sensor system;

wherein the machine controller collects image data of a location where currently generated sensor data and previously generated sensor data indicate a discontinuity in sensor data;

analyzes the image data to determine if a non-motion blur score for the image data is above a threshold value; and

adjusts a speed of the mobile machine based on a determination that the non-motion blur score is above the threshold value.

14. The mobile machine of claim 13 wherein the machine controller determines the location within an operating environment of the mobile machine where the discontinuity exists between the currently generated data and the previously generated data for the operating environment, selects the image data that corresponds to the location where the discontinuity exists between the currently generated data and the previously generated data for the operating environment, determines whether the a non-motion blur score for the selected image data is above the threshold value, determines that the operating environment includes an obscurant in response to a determination that the non-motion blur score for the selected image data is above the threshold value, and adjusts the speed of the mobile machine based on an optical density of the obscurant within the operating environment.

15. The mobile machine of claim 13 wherein the machine controller determines that an operating environment of the mobile machine includes an obstacle in response to a determination that the non-motion blur score for the image data is not above the threshold value, determines a type of the obstacle and a distance to the obstacle using the sensor system and a knowledge base associated with the mobile machine, and initiates an action for the mobile machine based on the type of and the distance to the obstacle.

16. The mobile machine of claim 13 wherein a sensor associated with the mobile machine emits pulses into an operating environment around the mobile machine and receives reflections of the pulses from objects in the operating environment, and wherein the machine controller generates current data for the operating environment based on the reflections of the pulses, compares the current data with the previously generated data for the operating environment, and determines whether continuity exists between the current data and the previously generated data.

17. The mobile machine of claim 14 wherein the obscurant is at least one of dust, fog, smoke, snow, rain, ash, or steam within the operating environment.

18. The mobile machine of claim 13 wherein the image data that corresponds to the location where the discontinuity exists between the currently generated data and the previously generated data is captured by an imaging device, and wherein the imaging device is a video camera.

19. The mobile machine of claim 13 wherein the machine controller adjusts the speed of the mobile machine by decreasing a maximum allowed speed of the mobile machine.

20. The mobile machine of claim 13 wherein the action is an avoidance maneuver.