Method of determining a collision avoidance maneuver
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
B60W-030/08
G08G-001/16
출원번호
US-0771737
(2007-06-29)
등록번호
US-7437246
(2008-10-14)
발명자
/ 주소
Kelly,Bradley D.
De Picciotto,Solomon A.
출원인 / 주소
Raytheon Company
대리인 / 주소
Lenzen, Jr.,Glenn H.
인용정보
피인용 횟수 :
4인용 특허 :
12
초록▼
A method of determining a collision avoidance maneuver includes obtaining initial state data including initial state data for a first object and a second object. A plurality of preliminary maneuvers satisfying a first set of constraints are generated using the initial state data. A best preliminary
A method of determining a collision avoidance maneuver includes obtaining initial state data including initial state data for a first object and a second object. A plurality of preliminary maneuvers satisfying a first set of constraints are generated using the initial state data. A best preliminary maneuver is selected from the plurality of preliminary maneuvers, and the best preliminary maneuver is optimized according to an objective function to provide a final maneuver. The optimization adheres to a provided second set of constraints.
대표청구항▼
What is claimed is: 1. A method of determining a collision avoidance maneuver, comprising: obtaining initial state data including initial state data for a first object and a second object; generating a plurality of preliminary maneuvers satisfying a first set of constraints using the initial state
What is claimed is: 1. A method of determining a collision avoidance maneuver, comprising: obtaining initial state data including initial state data for a first object and a second object; generating a plurality of preliminary maneuvers satisfying a first set of constraints using the initial state data; selecting a best preliminary maneuver from the plurality of preliminary maneuvers; and optimizing the best preliminary maneuver according to an objective function to provide a final maneuver, the optimization adhering to a provided second set of constraints. 2. The method of claim 1, wherein each preliminary maneuver has parameters further comprising an epoch and a delta velocity vector. 3. The method of claim 2, wherein selecting a best preliminary maneuver includes selecting a preliminary maneuver having the smallest delta velocity vector magnitude. 4. The method of claim 1, wherein each preliminary maneuver has parameters further comprising a start epoch, a thrust direction, and a burn duration. 5. The method of claim 4, wherein selecting a best preliminary maneuver includes selecting a preliminary maneuver having a shortest burn duration. 6. The method of claim 1, wherein the final maneuver has parameters further comprising an epoch and a delta velocity vector. 7. The method of claim 6, wherein the objective is to minimize a magnitude of the delta velocity vector. 8. The method of claim 1, wherein the final maneuver has parameters further comprising a start epoch, a thrust direction, and a burn duration. 9. The method of claim 8, wherein the objective is to minimize the burn duration. 10. The method of claim 1, wherein optimizing the best preliminary maneuver includes using a numerical optimizer subsystem. 11. The method of claim 1, wherein the initial state data further comprises: a first state vector associated with the first object and a second state vector associated with the second object; and a first covariance matrix associated with a position of the first object and a second covariance matrix associated with a position of the second object. 12. The method of claim 1, wherein the first set of constraints further comprises a first minimum miss distance constraint and a first probability of collision constraint. 13. The method of claim 12, wherein the first probability is a nominal probability determined by evaluating a relative covariance as a constant formed from a component covariance of the first object and a component covariance of the second object. 14. The method of claim 12, wherein the first probability is a maximum probability determined by evaluating a relative covariance along one dimension over a defined interval to scale against a component covariance of the first object and a component covariance of the second object. 15. The method of claim 12, wherein the first probability is a maximum probability determined by evaluating a relative covariance as a function of two variables, a first variable as a scale against a component covariance of the first object and a second variable as a scale against a component covariance of the second object. 16. The method of claim 1, wherein the second set of constraints further comprises a second minimum miss distance constraint, a second probability of collision constraint, and a maneuver time window. 17. The method of claim 16, wherein the second probability is a nominal probability determined by evaluating a relative covariance as a constant formed from a component covariance of the first object and a component covariance of the second object. 18. The method of claim 16, wherein the second probability is a maximum probability determined by evaluating a relative covariance along one dimension over a defined interval to scale against a component covariance of the first object and a component covariance of the second object. 19. The method of claim 16, wherein the second probability is a maximum probability determined by evaluating a relative covariance as a function of two variables, a first variable as a scale against a component covariance of the first object and a second variable as a scale against a component covariance of the second object. 20. The method of claim 16, wherein the second set of constraints further comprises a relative dot product value and a requirement that a difference consisting of a final maneuver execution time minus a time of closest approach be a positive value. 21. The method of claim 1, wherein the objective function specifies an optimizing objective. 22. The method of claim 1, wherein the objective function relates the second set of constraints to the final maneuver. 23. The method of claim 1 further comprising: analyzing a conjunction to determine a minimum miss distance and a probability of collision; and determining the collision avoidance maneuver only if the minimum miss distance is less than a first threshold or if the probability of collision exceeds a second threshold. 24. A method of determining a collision avoidance maneuver, comprising: obtaining initial state data including position data, position covariance data, and velocity data for a first object and a second object; determining a plurality of preliminary maneuvers, including the steps of: determining a plurality of points, each point having an unique combination of maneuver parameters including an epoch value, a yaw value, a pitch value, and a general maneuver direction; creating a preliminary maneuver from each point, each preliminary maneuver initially having a predetermined minimum delta velocity vector magnitude; simulating each preliminary maneuver and evaluating parameters constrained by a first set of constraints; and increasing the delta velocity vector magnitude of each preliminary maneuver in discrete steps until the preliminary maneuver adheres to the first set of constraints; designating a preliminary maneuver having a smallest delta velocity vector magnitude as a best preliminary maneuver; and optimizing the best preliminary maneuver according to an objective function to provide a final maneuver using a numerical optimizer subsystem, the final maneuver having about a smallest delta velocity vector magnitude allowing the final maneuver to adhere to a second set of constraints. 25. The method of claim 24, wherein the first set of constraints includes a first probability of collision determined; in a first instance as a nominal probability determined by evaluating a relative covariance as a constant formed from a component covariance of the first object and a component covariance of the second object; in a second instance as a maximum probability determined by evaluating a relative covariance along one dimension over a defined interval to scale against a component covariance of the first object and a component covariance of the second object; and in a third instance as a maximum probability determined by evaluating a relative covariance as a function of two variables, a first variable as a scale against a component covariance of the first object and a second variable as a scale against a component covariance of the second object; and the second set of constraints includes a second probability of collision determined; in a first instance as a nominal probability determined by evaluating a relative covariance as a constant formed from a component covariance of the first object and a component covariance of the second object; in a second instance as a maximum probability determined by evaluating a relative covariance along one dimension over a defined interval to scale against a component covariance of the first object and a component covariance of the second object; and in a third instance as a maximum probability determined by evaluating a relative covariance as a function of two variables, a first variable as a scale against a component covariance of the first object and a second variable as a scale against a component covariance of the second object. 26. A method of determining a collision avoidance maneuver, comprising: obtaining initial state data including position data, position covariance data, and velocity data for a first object and a second object; determining a plurality of preliminary maneuvers, including the steps of: determining a plurality of points, each point having an unique combination of maneuver parameters including a start epoch value, a yaw value, a pitch value, and a general maneuver direction; creating a preliminary maneuver from each point, each preliminary maneuver initially having a predetermined minimum burn duration; simulating each preliminary maneuver and evaluating parameters constrained by a first set of constraints; and increasing the burn duration of each preliminary maneuver in discrete steps until the preliminary maneuver adheres to the first set of constraints; designating a preliminary maneuver having a shortest burn duration as a best preliminary maneuver; and optimizing the best preliminary maneuver according to an objective function to provide a final maneuver using a numerical optimizer subsystem, the final maneuver having about a shortest burn duration allowing the final maneuver to adhere to a second set of constraints. 27. The method of claim 26, wherein the first set of constraints includes a first probability of collision determined; in a first instance as a nominal probability determined by evaluating a relative covariance as a constant formed from a component covariance of the first object and a component covariance of the second object; in a second instance as a maximum probability determined by evaluating a relative covariance along one dimension over a defined interval to scale against a component covariance of the first object and a component covariance of the second object; and in a third instance as a maximum probability determined by evaluating a relative covariance as a function of two variables, a first variable as a scale against a component covariance of the first object and a second variable as a scale against a component covariance of the second object; and the second set of constraints includes a second probability of collision determined; in a first instance as a nominal probability determined by evaluating a relative covariance as a constant formed from a component covariance of the first object and a component covariance of the second object; in a second instance as a maximum probability determined by evaluating a relative covariance along one dimension over a defined interval to scale against a component covariance of the first object and a component covariance of the second object; and in a third instance as a maximum probability determined by evaluating a relative covariance as a function of two variables, a first variable as a scale against a component covariance of the first object and a second variable as a scale against a component covariance of the second object. 28. A computer system for determining a collision avoidance maneuver, comprising: a processing unit; a memory storage device coupled to the processing unit; an input device coupled to the processing unit; an output device coupled to the processing unit; the processing unit being operative to: obtain initial state data including initial state data for a first object and a second object; generate a plurality of preliminary maneuvers satisfying a first set of constraints using the initial state data; select a best preliminary maneuver from the plurality of preliminary maneuvers; and optimize the best preliminary maneuver according to an objective function to provide a final maneuver, the optimization adhering to a provided second set of constraints. 29. A software product comprising instructions, stored on computer-readable media, wherein the instructions, when executed by a computer, perform steps for determining a collision avoidance maneuver, comprising: an input routine operatively associated with an input device for obtaining initial state data including initial state data for a first object and a second object; a preliminary maneuver generating routine for generating a plurality of preliminary maneuvers satisfying a first set of constraints using the initial state data; a selection routine for selecting a best preliminary maneuver from the plurality of preliminary maneuvers; and an optimizing routine for optimizing the best preliminary maneuver according to an objective function to provide a final maneuver, the optimization routine adhering to a provided second constraint. 30. The software product of claim 21, wherein multiple instantiations of the routines execute substantially concurrently.
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