Title :
Using co-evolution to produce robust robot control
Author_Institution :
Sun Microsyst. Inc., Palo Alto, CA, USA
Abstract :
Genetic programming is used to co-evolve robots and their test environments. Simulated mobile robots evolved based on their ability to navigate test courses. Test courses evolve based on their ability to cause robots to crash. Coupling robots to their test environments produces robust results. Co-evolution simultaneously evolves the robot controller, verifies the robot physical design and tests the robots in increasingly difficult environments. The robots produced can routinely navigate over 98% of these highly evolved, difficult test courses. In several cases, robots are found that navigate 100% of the courses
Keywords :
genetic algorithms; mobile robots; robot programming; robust control; co-evolution; genetic programming; physical design verifcation; robust robot control; simulated mobile robots; test environments; Computer crashes; Genetic programming; Mobile robots; Navigation; Robot control; Robot sensing systems; Robust control; Robustness; Sun; Vehicle crash testing;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.657684