SYSTEM AND METHOD FOR EVALUATION OF OBJECT AUTONOMY

• US 20160321381A1
• Filed: 04/29/2016
• Published: 11/03/2016
• Est. Priority Date: 04/29/2015
• Status: Active Grant

• Current Assignee: Universal Robots USA Incorporated
• Original Assignee: Energid Technologies Corporation (Teradyne Incorporated)
• Inventors: ENGLISH, JAMES D., Penning, Ryan S., Barker, Douglas E., Bacon, James A.
• Granted Patent: US 10,635,761 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05B 2219/23446 HIL hardware in the loop, simulates equipment to which a control module is fixed
• 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
• CPC Class Codes: G06F 2111/08 Probabilistic or stochastic CAD
• CPC Class Codes: G06F 2111/10 Numerical modelling
• CPC Class Codes: G06F 30/15 Vehicle, aircraft or watercraft design
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A method, computer program product, and computer system for configuring a stochastic simulation scenario, wherein the stochastic simulation scenario may include one or more variables without a complete probability distribution. The stochastic simulation scenario may be executed to generate one or more results of the stochastic simulation scenario. At least a portion of the one or more variables without the probability distribution may be optimized using one or more optimization metrics on the one or more results of the stochastic simulation scenario.

Claims

1. A computer-implemented method comprising:

configuring, by a computing device, a stochastic simulation scenario, wherein the stochastic simulation scenario includes one or more variables without a complete probability distribution;

executing the stochastic simulation scenario to generate one or more results of the stochastic simulation scenario; and

optimizing at least a portion of the one or more variables without the probability distribution using one or more optimization metrics on the one or more results of the stochastic simulation scenario.

2. The computer-implemented method of claim 1 wherein the stochastic simulation scenario is randomized and digital.

3. The computer-implemented method of claim 1 wherein the stochastic simulation scenario includes hardware-in-the-loop architecture associated with the stochastic simulation scenario.

4. The computer-implemented method of claim 1 wherein the stochastic simulation scenario includes at least one of:

a land vehicle, an air vehicle, and a water vehicle;

one or more fixed base articulated robot arms; and

one or more mobile articulated robot arms mounted on at least one of the land vehicle, the air vehicle, and the water vehicle.

5. The computer-implemented method of claim 1 wherein the stochastic simulation scenario includes an autonomous convoy.

6. The computer-implemented method of claim 1 wherein the one or more optimization metrics includes a threshold measure of variance.

7. The computer-implemented method of claim 1 wherein the stochastic simulation scenario uses Monte Carlo analysis.

8. The computer-implemented method of claim 1 wherein the stochastic simulation scenario includes at least one of an orbit, an asteroid, a comet, a planet, and a moon.

9. A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:

configuring a stochastic simulation scenario, wherein the stochastic simulation scenario includes one or more variables without a complete probability distribution;

executing the stochastic simulation scenario to generate one or more results of the stochastic simulation scenario; and

optimizing at least a portion of the one or more variables without the probability distribution using one or more optimization metrics on the one or more results of the stochastic simulation scenario.

10. The computer program product of claim 9 wherein the stochastic simulation scenario is randomized and digital.

11. The computer program product of claim 9 wherein the stochastic simulation scenario includes hardware-in-the-loop architecture associated with the stochastic simulation scenario.

12. The computer program product of claim 9 wherein the stochastic simulation scenario includes at least one of:

a land vehicle, an air vehicle, and a water vehicle;

one or more fixed base articulated robot arms; and

one or more mobile articulated robot arms mounted on at least one of the land vehicle, the air vehicle, and the water vehicle.

13. The computer program product of claim 9 wherein the stochastic simulation scenario includes an autonomous convoy.

14. The computer program product of claim 9 wherein the one or more optimization metrics includes a threshold measure of variance.

15. The computer program product of claim 9 wherein the stochastic simulation scenario uses Monte Carlo analysis.

16. The computer program product of claim 9 wherein the stochastic simulation scenario includes at least one of an orbit, an asteroid, a comet, a planet, and a moon.

17. A computing system including one or more processors and one or more memories configured to perform operations comprising:

configuring a stochastic simulation scenario, wherein the stochastic simulation scenario includes one or more variables without a complete probability distribution;

executing the stochastic simulation scenario to generate one or more results of the stochastic simulation scenario; and

optimizing at least a portion of the one or more variables without the probability distribution using one or more optimization metrics on the one or more results of the stochastic simulation scenario.

18. The computing system of claim 17 wherein the stochastic simulation scenario is randomized and digital.

19. The computing system of claim 17 wherein the stochastic simulation scenario includes hardware-in-the-loop architecture associated with the stochastic simulation scenario.

20. The computing system of claim 17 wherein the stochastic simulation scenario includes at least one of:

a land vehicle, an air vehicle, and a water vehicle;

one or more fixed base articulated robot arms; and

one or more mobile articulated robot arms mounted on at least one of the land vehicle, the air vehicle, and the water vehicle.

21. The computing system of claim 17 wherein the stochastic simulation scenario includes an autonomous convoy.

22. The computing system of claim 17 wherein the one or more optimization metrics includes a threshold measure of variance.

23. The computing system of claim 17 wherein the stochastic simulation scenario uses Monte Carlo analysis.

24. The computing system of claim 17 wherein the stochastic simulation scenario includes at least one of an orbit, an asteroid, a comet, a planet, and a moon.