Chaos genetic algorithm based path planning method for mobile robot

Abstract

Combing the inversion property of the genetic algorithm with the ergodic property of the chaos optimization method, the path planning method based on a chaos genetic algorithm for mobile robot can improve the local search ability and search accuracy of genetic algorithm, and then effectively avoid the common defect of early convergence when using a simple genetic algorithm in path planning problems. Simulation results show that the method can converge on the global optimum path under both sparse and dense environments and is more robust to the robot workspace.