System and method for evaluation of object autonomy
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.
1. A computer-implemented method comprising:
configuring, by a computing device, a stochastic simulation scenario, wherein the stochastic simulation scenario is randomized and digital, includes hardware-in-the-loop architecture associated with the stochastic simulation scenario, and includes one or more variables without a complete probability distribution, wherein the one or more variables without a complete probability distribution includes human activity with an unknowable 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 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.
3. The computer-implemented method of claim 1 wherein the stochastic simulation scenario includes an autonomous convoy.
4. The computer-implemented method of claim 1 wherein the one or more optimization metrics includes a threshold measure of variance.
5. The computer-implemented method of claim 1 wherein the stochastic simulation scenario uses Monte Carlo analysis.
6. 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.
7. The computer-implemented method of claim 1 wherein optimizing at least a portion of the one or more variables includes optimizing over multiple parameters to enable competing objective functions.
8. A non-transitory 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 is randomized and digital, includes hardware-in-the-loop architecture associated with the stochastic simulation scenario, and includes one or more variables without a complete probability distribution, wherein the one or more variables without a complete probability distribution includes human activity with an unknowable 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.
9. The computer program product of claim 8 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.
10. The computer program product of claim 8 wherein the stochastic simulation scenario includes an autonomous convoy.
11. The computer program product of claim 8 wherein the one or more optimization metrics includes a threshold measure of variance.
12. The computer program product of claim 8 wherein the stochastic simulation scenario uses Monte Carlo analysis.
13. The computer program product of claim 8 wherein the stochastic simulation scenario includes at least one of an orbit, an asteroid, a comet, a planet, and a moon.
14. The computer program product of claim 8 wherein optimizing at least a portion of the one or more variables includes optimizing over multiple parameters to enable competing objective functions.
15. 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 is randomized and digital and includes one or more variables without a complete probability distribution, wherein the one or more variables without a complete probability distribution includes human activity with an unknowable 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, wherein optimizing includes an optimization algorithm held within an XML-specified class.
16. The computing system of claim 15 wherein the stochastic simulation scenario includes hardware-in-the-loop architecture associated with the stochastic simulation scenario.
17. The computing system of claim 15 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.
18. The computing system of claim 15 wherein the stochastic simulation scenario includes an autonomous convoy.
19. The computing system of claim 15 wherein the one or more optimization metrics includes a threshold measure of variance.
20. The computing system of claim 15 wherein the stochastic simulation scenario uses Monte Carlo analysis.
21. The computing system of claim 15 wherein the stochastic simulation scenario includes at least one of an orbit, an asteroid, a comet, a planet, and a moon.
22. The computing system of claim 15 wherein optimizing at least a portion of the one or more variables includes optimizing over multiple parameters to enable competing objective functions.