Robot Path planning based on improved genetic algorithm
Yuan Fang Zhao, Jason J. Gu · 2013
This paper proposes an environment model based on grid, and comes up with a two-layer genetic algorithm mechanism as global parallel optimize searching tool to find optimal path. The first layer is responsible for static obstacles avoidance, while the second layer is responsible for dynamic obstacles avoidance, and these two-layer genetic algorithm mechanism has different fitness functions. Simulation results prove the feasibility and effectiveness of the proposed algorithm.