SWARM
Multi-robot Path Planning Based on Cooperative Co-evolution and Adaptive CGA
Jinyin Chen, Dongyong Yang, Naofumi Matsumoto, Yuzo Yamane
- Year
- 2006
- Citations
- 7
Abstract
Multi-robot path planning is a challenge for mobile robots in AI. Multi-objective optimized algorithm based on cooperative co-evolution and CGA is brought up in this paper. Shortest path length, minimum time cost, smoothest and limited speed, obstacle-collide free and robot-collide free are the objectives and constraints to optimize. Linear combination of them is designed as evaluation function for CGA with self-adaptive crossover and mutation rate, combined with chaos disturbs. Finally 2D dynamic simulation has proved the efficiency of the algorithm.
Keywords
CrossoverMotion planningMobile robotObstacleRobotPath (computing)Computer scienceMathematical optimizationObstacle avoidanceFunction (biology)
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