System and method for describing and executing behaviors in autonomous and semi-autonomous devices
A system and method of describing and executing autonomous or autonomous device behaviors via a computer-implemented system incorporating a fuzzy language, a simulator, and one or more runtimes. The fuzzy language combines high level behaviors and produces a set of parameter descriptions. The parameter descriptions are behavior characteristics whose values are not yet necessarily known or selected. The parameter descriptions are used via simulation to find relevant parameters and acceptable parameter values that result or will result in the autonomous or semi-autonomous device behaving as desired.
1. A computer-implemented method of describing and executing behaviors of an autonomous or semi-autonomous device, the computer-implemented method comprising:
receiving a behavior source file;
compiling the behavior source file into an intermediary executable file and a set of parameter descriptions;
linking the intermediary executable file with a simulator so as to produce an executable file;
running the executable file in conjunction with the parameter descriptions in the simulator so as to find acceptable parameter values via a simulation;
compiling the intermediary executable file, a runtime of the autonomous or semi-autonomous device, and the acceptable parameter values so as to produce an executable control program; and
controlling the autonomous or semi-autonomous device according to the executable control program so that the autonomous or semi-autonomous device behaves according to the acceptable parameter values.
2. The computer-implemented method of claim 1 , wherein at least some of the parameter values are coefficients, the step of running the executable file in conjunction with the parameter descriptions to find acceptable parameter values including finding coefficients via a Monte Carlo search.
3. The computer-implemented method of claim 2 , further comprising identifying a number of clusters of potential parameters, selecting a best parameter set from each cluster, and selecting a best overall parameter set.
4. The computer-implemented method of claim 3 , further comprising testing the best parameter sets via the autonomous or semi-autonomous device to select the best overall parameter set.
5. The computer-implemented method of claim 3 , further comprising testing the best parameter sets by entering the best parameter sets into the simulation.
6. The computer-implemented method of claim 1 , wherein the step of running the executable file in conjunction with the parameter descriptions includes running an amoeba search to find the acceptable parameter values.
7. The computer-implemented method of claim 1 , wherein the step of running the executable file in conjunction with the parameter descriptions in the simulator includes simulating the autonomous or semi-autonomous device and an environment of the autonomous or semi-autonomous device.
8. The computer-implemented method of claim 1 , further comprising the step of passing some of the parameter values to the executable control program at run time.
9. The computer-implemented method of claim 1 , further comprising the step of modifying some of the parameter values at run time.
10. The computer-implemented method of claim 1 , wherein some of the parameter values are human-selected.
11. A computer-implemented system for describing and executing behaviors of an autonomous or semi-autonomous device, the computer-implemented system comprising:
a processor configured to:
receive a behavior source file;
compile the behavior source file into an intermediary executable file and a set of parameter descriptions;
link the intermediary executable file with a simulator so as to produce an executable file;
run the executable file in conjunction with the parameter descriptions in the simulator so as to find acceptable parameter values via a simulation;
compile the intermediary executable file, a runtime of the autonomous or semi-autonomous device, and the acceptable parameter values so as to produce an executable control program; and
control the autonomous or semi-autonomous device according to the executable control program so that the autonomous or semi-autonomous device behaves according to the acceptable parameter values.
12. The computer-implemented system of claim 11 , wherein at least some of the parameter values are coefficients, the processor being further configured to find the coefficients via a Monte Carlo search.
13. The computer-implemented system of claim 12 , wherein the processor is further configured to identify a number of clusters of potential parameters, select a best parameter set from each cluster, and select a best overall parameter set.
14. The computer-implemented system of claim 13 , wherein the processor is further configured to test the best parameter sets via the autonomous or semi-autonomous device to select the best overall parameter set.
15. The computer-implemented system of claim 13 , wherein the processor is further configured to test the best parameter sets by entering the best parameter sets into the simulation.
16. The computer-implemented system of claim 11 , wherein the processor is further configured to run an amoeba search to find the acceptable parameter values.
17. The computer-implemented system of claim 11 , wherein the processor is further configured to simulate the autonomous or semi-autonomous device and an environment of the autonomous or semi-autonomous device.
18. The computer-implemented system of claim 11 , wherein the processor is further configured to pass some of the parameter values to the executable control program at run time.
19. The computer-implemented system of claim 11 , wherein the processor is further configured to modify some of the parameter values at run time.
20. The computer-implemented system of claim 11 , wherein the processor is further configured to receive human-selected parameter values.