Obstacle detection method and system

• US 20090259399A1
• Filed: 04/15/2008
• Published: 10/15/2009
• Est. Priority Date: 04/15/2008
• Status: Abandoned Application

• Current Assignee: Caterpillar Incorporated
• Original Assignee: Caterpillar Incorporated
• Inventors: Edwards, David, Kotejoshyer, Badari
• Application Number:
  US12/081,346
• Publication Number:
  US 20090259399A1
• Time in Patent Office: Days
• US Class Current: 701/300
• CPC Class Codes: G01S 13/87 Combinations of radar systems, e.g. primary radar and secondary radar
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 2013/9315 Monitoring blind spots
• CPC Class Codes: G01S 7/4802 using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G08G 1/16 Anti-collision systems road vehicle drive control systems for predicting or avoiding probable or impending collision otherwise than by control of a particular sub-unit B60W30/08

Abstract

A system for detecting obstacles near a machine is disclosed. The system has a plurality of obstacle sensors located on the machine. The system also has a controller in communication with each of the plurality of obstacle sensors. The controller is configured to pair one-to-one each of the plurality of obstacle sensors to each of a plurality of non-overlapping confidence regions. Additionally, the controller is configured to scan with the plurality of obstacle sensors. The controller is also configured to receive from the plurality of obstacle sensors raw data regarding the scanning, and assemble the raw data into a map. Based on the map, the controller is configured to determine at least one characteristic of at least one obstacle.

Claims

1. A method for detecting obstacles near a machine, comprising:

pairing one-to-one each of a plurality of obstacle sensors to each of a plurality of non-overlapping confidence regions;

scanning with the plurality of obstacle sensors;

receiving from the plurality of obstacle sensors raw data regarding the scanning;

assembling the raw data into a map; and

determining at least one characteristic of at least one obstacle, based on the map.

2. The method of claim 1, wherein assembling the raw data into a map includes transforming the raw data from each of the plurality of obstacle sensors into useable data.

3. The method of claim 2, wherein transforming the raw data from each of the plurality of obstacle sensors into useable data includes applying a coordinate transform specific to each of the plurality of obstacle sensors to the raw data from each of the plurality of obstacle sensors.

4. The method of claim 2, wherein transforming the raw data from each of the plurality of obstacle sensors into useable data includes applying a confidence region filter specific to each of the plurality of obstacle sensors to the raw data from each of the plurality of obstacle sensors.

5. The method of claim 2, wherein assembling the raw data into a map includes unionizing the usable data from each of the plurality of obstacle sensors.

6. The method of claim 1, wherein the map includes a sets of surface points.

7. The method of claim 6, wherein determining at least one characteristic of at least one obstacle includes determining a size of at least one obstacle.

8. The method of claim 7, wherein determining the size of at least one obstacle, includes applying a height filter to the set of surface points.

9. The method of claim 8, wherein the height filter removes a point that is within a certain distance from a predicted ground surface from the set of surface points.

10. The method of claim 7 wherein determining the size of at least one obstacle, further includes converting at least two of the surface points into at least one obstacle.

11. The method of claim 10, wherein determining the size of at least one obstacle, further includes applying a size filter to the at least one obstacle.

12. The method of claim 11, wherein the size filter retains at least one obstacle that has a height longer than a certain length.

13. The method of claim 11, wherein the size filter retains at least one obstacle that has a width longer than a certain length.

14. The method of claim 11, wherein the size filter retains at least one obstacle that has a depth longer than a certain length.

15. A system for detecting obstacles near a machine, comprising:

a plurality of obstacle sensors located on the machine; and

a controller in communication with each of the plurality of obstacle sensors, and configured to;

pair one-to-one each of the plurality of obstacle sensors to each of a plurality of non-overlapping confidence regions;

scan with the plurality of obstacle sensors;

receive from the plurality of obstacle sensors raw data regarding the scanning;

assemble the raw data into a map; and

determine at least one characteristic of at least one obstacle, based on the map.

16. The system of claim 15, wherein the map is electronic in form and stored within a memory of the controller.

17. The system of claim 16, wherein the map includes a set of surface points.

18. The system of claim 17, wherein determining at least one characteristic of at least one obstacle includes determining a size of at least one obstacle.

19. The system of claim 15, wherein the confidence regions are volumetric regions.

20. The system of claim 15, wherein assembling the raw data into a map includes transforming the raw data from each of the plurality of obstacle sensors into useable data.