Cooperative control of unmanned aerial vehicles for tracking targets

• US 8,639,396 B1
• Filed: 10/07/2009
• Issued: 01/28/2014
• Est. Priority Date: 10/08/2008
• Status: Active Grant

• Current Assignee: Raytheon Company (Rtx Corporation)
• Original Assignee: Raytheon Company (Rtx Corporation)
• Inventors: Hirsch, Michael J., Eck, Christopher R., Ortiz Pena, Hector J.
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): PIPALA, EDWARD J
• Application Number:
  US12/575,201
• Time in Patent Office: 1,574 Days
• Field of Search: 701/1, 701/2, 701/3, 701/11, 701/23, 701/400, 701/408, 701/409, 701/410, 701/422, 701/423, 701466-469, 701/24, 701/26, 701/516, 701/519, 701/300, 701/4, 701/14, 701/25, 701/28, 701/118, 701/119, 701/120, 701/122, 701/411, 701/416, 701/418, 348/148, 348/153, 348/159, 348/143, 348/149, 244/189, 244/190, 244/175, 382/100, 382/103, 340/988, 340/995.12, 340/995.13, 340/995.19
• US Class Current: 701/3
• CPC Class Codes: G05D 1/0094 involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: G08G 5/0008 with other aircraft
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft

Abstract

In certain embodiments, a method includes accessing first target information associated with a first target visible to a first UAV at a first time and accessing second target information, received from a neighboring UAV, associated with a second target visible to the neighboring UAV at the first time. The method further includes combining the first target information and the second target information to generate combined target information and determining, based on the combined target information, a predicted location for the first and second targets at a second time. The method further includes determining a planned route for the first UAV for the second time by solving an optimization problem, the optimization problem accounting for the determined predicted location for the first and second targets, kinematic constraints associated with the first UAV and the neighboring UAV, and line-of-sight constraints associated with the first UAV and the neighboring UAV.

Claims

1. A method, comprising:

accessing, using one or more processing units, first target information associated with a first target visible to a first UAV at a first time;

accessing, using one or more processing units, second target information, received from a neighboring UAV, associated with a second target visible to the neighboring UAV at the first time;

combining the first target information and the second target information to generate combined target information for the first time;

determining, based on the combined target information, a predicted location for the first and second targets at a second time;

determining a planned route for the first UAV for the second time by solving an optimization problem, the optimization problem accounting for the determined predicted location for the first and second targets and a plurality of constraints comprising;

kinematic constraints associated with the first UAV and the neighboring UAV; and

line-of-sight constraints associated with the first UAV and the neighboring UAV, wherein the line-of-sight constraints associated with the first UAV and the neighboring UAV correspond to one or more objects that obstruct a line-of-sight of at least one of the first UAV and the neighboring UAV.

2. The method of claim 1, wherein solving the optimization problem comprises minimizing a sum of determinants of covariances for each of the first and second targets over a time interval from the first time to the second time.

3. The method of claim 2, wherein the sum of the determinants of the covariances for each of the first and second targets is weighted with an importance function, the importance function defining one or more regions for which accurate first and second target information for the first and second targets is of increased importance.

4. The method of claim 1, wherein solving the optimization problem comprises using a continuous Greedy Randomized Adaptive Search Procedure (GRASP).

5. The method of claim 1, comprising:

generating, prior to determining the predicted location for each of the first and second targets at the second time, a qualitative score for the combined target information; and

determining whether the generated score is greater than a predetermined minimum score.

6. The method of claim 1, wherein the kinematic constraints associated with the first UAV and the neighboring UAV comprises one or more of a minimum turning radius, a minimum speed, and a maximum speed.

7. The method of claim 1, wherein the line-of-sight constraints associated with the first UAV and the neighboring UAV correspond to one or more buildings in an urban environment that obstruct the line-of-sight of at least one of the first UAV and the neighboring UAV.

8. The method of claim 1, wherein the first target and the second target are the same.

9. The method of claim 1, wherein the first target is visible to the first UAV such that the first target is directly detectable by the first UAV.

10. A system, comprising:

one or more processing units operable to;

access first target information associated with a first target visible to a first UAV at a first time;

access second target information, received from a neighboring UAV, associated with a second target visible to the neighboring UAV at the first time;

combine the first target information and the second target information to generate combined target information for the first time;

determine, based on the combined target information, a predicted location for the first and second targets at a second time;

determine a planned route for the first UAV for the second time by solving an optimization problem, the optimization problem accounting for the determined predicted location for the first and second targets and a plurality of constraints comprising;

kinematic constraints associated with the first UAV and the neighboring UAV; and

line-of-sight constraints associated with the first UAV and the neighboring UAV, wherein the line-of-sight constraints associated with the first UAV and the neighboring UAV correspond to one or more objects that obstruct a line-of-sight of at least one of the first UAV and the neighboring UAV.

11. The system of claim 10, wherein solving the optimization problem comprises minimizing a sum of determinants of covariances for each of the first and second targets over a time interval form the first time to the second time.

12. The system of claim 11, wherein the sum of the determinants of the covariances for each of the first and second targets is weighted with an importance function, the importance function defining one or more regions for which accurate first and second target information for the first and second targets is of increased importance.

13. The system of claim 10, wherein solving the optimization problem comprises using a continuous Greedy Randomized Adaptive Search Procedure (GRASP).

14. The system of claim 10, wherein the one or more processing units are operable to:

generate, prior to determining the predicted location for each of the first and second targets at the second time, a qualitative score for the combined target information; and

determine whether the generated score is greater than a predetermined minimum score.

15. The system of claim 10, wherein the kinematic constraints associated with the first UAV and the neighboring UAV comprises one or more of a minimum turning radius, a minimum speed, and a maximum speed.

16. The system of claim 10, wherein the line-of-sight constraints associated with the first UAV and the neighboring UAV correspond to one or more buildings in an urban environment that obstruct the line-of-sight of at least one of the first UAV and the neighboring UAV.

17. The system of claim 10, wherein the first target and the second target are the same.

18. The system of claim 10, wherein the first target is visible to the first UAV such that the first target is directly detectable by the first UAV.

19. A non-transitory, computer-readable medium having computer readable instructions stored thereon that, when executed by a computer, implement a method, comprising:

accessing first target information associated with a first target visible to a first UAV at a first time;

accessing second target information, received from a neighboring UAV, associated with a second target visible to the neighboring UAV at the first time;

combining the first target information and the second target information to generate combined target information for the first time;

determining, based on the combined target information, a predicted location for the first and second targets at a second time;

determining a planned route for the first UAV for the second time by solving an optimization problem, the optimization problem accounting for the determined predicted location for the first and second targets and a plurality of constraints comprising;

kinematic constraints associated with the first UAV and the neighboring UAV; and

line-of-sight constraints associated with the first UAV and the neighboring UAV, wherein the line-of-sight constraints associated with the first UAV and the neighboring UAV correspond to one or more objects that obstruct a line-of-sight of at least one of the first UAV and the neighboring UAV.

20. The computer-readable medium of claim 19, wherein solving the optimization problem comprises minimizing a sum of determinants of covariances for each of the first and second targets over a time interval from the first time to the second time.

21. The computer-readable medium of claim 20, wherein the sum of the determinants of the covariances for each of the first and second targets is weighted with an importance function, the importance function defining one or more regions for which accurate first and second target information for the first and second targets is of increased importance.

22. The computer-readable medium of claim 19, wherein solving the optimization problem comprises using a continuous Greedy Randomized Adaptive Search Procedure (GRASP).

23. The computer-readable medium of claim 19, wherein the software is operable to perform operations comprising:

generating, prior to determining the predicted location for each of the first and second targets at the second time, a qualitative score for the combined target information; and

determining whether the generated score is greater than a predetermined minimum score.

24. The computer-readable medium of claim 19, wherein the kinematic constraints associated with the first UAV and the neighboring UAV comprises one or more of a minimum turning radius, a minimum speed, and a maximum speed.

25. The computer-readable medium of claim 19, wherein the line-of-sight constraints associated with the first UAV and the neighboring UAV correspond to one or more buildings in an urban environment that obstruct the line-of-sight of at least one of the first UAV and the neighboring UAV.

26. The computer-readable medium of claim 19, wherein the first target and the second target are the same.

27. The computer-readable medium of claim 19, wherein the first target is visible to the first UAV such that the first target is directly detectable by the first UAV.