NEGATIVE OBSTACLE DETECTOR

• US 20170176990A1
• Filed: 12/18/2015
• Published: 06/22/2017
• Est. Priority Date: 12/18/2015
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Becker, John R., Keller, Sean D., Uyeno, Gerald P.
• Granted Patent: US 9,946,259 B2
• Time in Patent Office: Days
• CPC Class Codes: G01S 17/42 Simultaneous measurement of distance and other co-ordinates indirect measurement G01S17/46
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 7/4802 using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G01S 7/4817 relating to scanning
• 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

Abstract

An obstacle detector configured to identify negative obstacles in a vehicle'"'"'s path responsive to steering a laser beam to scan high priority areas in the vehicle'"'"'s path is provided. The high priority areas can be identified dynamically in response to the terrain, speed, and/or acceleration of the vehicle. In some examples, the high priority areas are identified based on a projected position of the vehicles tires. A scan path for the laser, scan rate, and/or a scan location can be dynamically generated to cover the high priority areas.

Claims

1. An obstacle detector comprising:

a laser scanner device including;

an optical source configured to emit a laser beam;

a steering device configured to steer the laser beam from the optical source over a field of regard of the laser scanner device according to a discrete scan pattern; and

a range detector that generates range information based on receiving a reflection of the laser beam and determines an intensity of the reflection of the laser beam; and

at least one processor operatively connected to the steering device and to the range detector and configured to;

define the discrete scan pattern;

direct the steering device to steer the laser beam over the field of regard according to the scan pattern; and

identify an indicator of at least one negative obstacle using the intensity of the reflection of the laser beam and the range information generated by the range detector.

2. The obstacle detector of claim 1, wherein the steering device comprises a solid-state liquid crystal waveguide (LCWG).

4. The obstacle detector of claim 1, wherein the at least one processor is configured to validate the indicator of the negative obstacle responsive to subsequent scanning of a region of the field of regard in which the indicator was detected.

5. The obstacle detector of claim 4, wherein the at least one processor is configured to evaluate the intensity of the reflection of the laser beam corresponding to a candidate obstacle to validate the indicator of the negative obstacle.

6. The obstacle detector of claim 1, wherein the optical source is configured to emit multiple wavelengths, and wherein the at least one processor is further configured to identify the indicator responsive to correlating reflections of the multiple wavelengths.

7. The obstacle detector of claim 1, wherein the obstacle detector is disposed on an autonomous vehicle;

and wherein at least one processor is configured to define the scan pattern responsive to analyzing at least one of terrain information, vehicle information, information from an inertial navigation system (INS) disposed on the autonomous vehicle, and information from a GPS unit disposed on the autonomous vehicle, and an estimated a travel path for the autonomous vehicle.

8. The obstacle detector of claim 7, wherein the at least one processor is configured to:

estimate a position for one or more portions of the autonomous vehicle that contact terrain based on the estimated travel path; and

define the scan pattern to cover at least the estimated position for the one or more portions of the autonomous vehicle that contact the terrain.

10. The obstacle detector of claim 8, wherein the at least one processor is configured to generate control signals to manage steering of the steering device according to the scan pattern.

11. The obstacle detector of claim 10, wherein the at least one processor is further configured to define a scan frequency for high-speed rescanning of candidate obstacles.

12. The obstacle detector of claim 1, wherein the at least one processor is further configured to select a range gate associated with the range detector from a plurality of range gates;

wherein the at least one processor triggers;

a first range gate for capturing general characteristics of a scan surface;

a second range gate and a bit depth increase for detecting perturbations in the scan surface, the second range gate being smaller than the first range gate; and

a third range gate to plot slopes of the scan surface or detect differences in heights of the scan surface, the third range gate being larger than the second range gate.

13. The obstacle detector of claim 29, wherein the at least one processor is configured to reduce a scan area associated with the scan pattern responsive to an increase in the vehicle speed or a decrease in the vehicle speed of the autonomous vehicle.

14. The obstacle detector of claim 8, wherein the at least one processor is configured to dynamically adjust a base scan pattern to emphasize priority areas in the field of regard of the laser scanner device, wherein the priority areas are identified by the at least one processor responsive to determining an estimated position for one or more portions of the autonomous vehicle that contact ground.

15. The obstacle detector of claim 7, wherein the at least one processor is configured to analyze multiple reflections of the laser beam to:

identify intensity differences to determine a location of the laser beam on a path;

identify range differences to determine the location of an obstacle edge;

correlate size change of a negative obstacle relative to sample time;

identify regions free of negative obstacles responsive to scan information, including a scan area for a single wheel and scan information captured on another discrete area based on a distance offset associated with a second wheel; and

identify positive obstacles larger than ground clearance associated with the vehicle.

29. The obstacle detector of claim 11, wherein at least one processor is configured to tailor the definition of the scan pattern responsive to vehicle speed of the autonomous vehicle.

3. (canceled)

9. (canceled)

16. A method of detecting a negative obstacle, the method comprising:

emitting, by an optical source, a laser beam;

directing, by a steering device, the laser beam over a scan area within a field of regard according to a discrete scan pattern;

defining, by at least one processor, the discrete scan pattern;

receiving, with a range detector, a reflection of the laser beam from the scan area;

processing, with the at least one processor, the reflection of the laser beam to determine range data and intensity information; and

identifying, by the at least one processor, at least one negative obstacle responsive to the range data and the intensity information.

20. The method of claim 16, further comprising re-scanning a region of the scan area to validate identification of the at least one negative obstacle.

22. The method of claim 16, wherein the act of defining the discrete scan pattern includes defining the discrete scan pattern responsive to analyzing one or more of:

terrain information, vehicle information, and an estimated travel path for an autonomous vehicle on which the optical source, the steering device, and the at least one processor are located.

23. The method of claim 22, further comprising estimating the travel path for the autonomous vehicle by estimating a position for one or more portions of the autonomous vehicle that contact terrain based on the terrain information.

25. The method of claim 23, wherein defining the discrete scan pattern includes:

defining a location and a scan frequency for high-speed rescanning of candidate obstacles; and

tailoring the definition of the scan pattern responsive to vehicle speed.

26. The method of claim 16, further comprising tailoring a range gate associated with the range detector including:

establishing a first range gate for capturing general characteristics of a scan surface;

establishing a second range gate and a bit depth increase for detecting perturbations in the scan surface, the second range gate being smaller than the first range gate; and

establishing a third range gate to plot slopes of the scan surface or detect differences in relative height of sections of the scan surface, the third range gate being larger than the second range gate.

27. The method of claim 23, further comprising analyzing return signals corresponding to reflections of the laser beam and at least one of:

identifying intensity differences in the return signals to determine a location of the laser beam on a path responsive to analyzing the return signals;

identifying range differences to determine the location of an obstacle edge responsive to analyzing the return signals;

correlating size change of a negative obstacle relative to sample time responsive to analyzing the return signals;

identifying regions free of negative obstacles responsive to scan information, including a scan area for a single wheel and scan information captured on another discrete area based on a distance offset associated with a second wheel, responsive to analyzing the return signals;

or

identifying positive obstacles larger than ground clearance associated with the vehicle, responsive to analyzing the return signals.

28. The method of claim 23, wherein defining the scan pattern includes defining the scan pattern to cover at least the estimated position for the one or more portions of the autonomous vehicle that contact the terrain

17. (canceled)

18. The method of claim 17, wherein the act of identifying includes acts of:

analyzing multiple wavelengths in the reflection of the laser beam, and

identifying negative obstacles responsive to correlating returns from the multiple wavelengths.

19. (canceled)

21. (canceled)

24. (canceled)