Abstract: Based on artificial potential field and grid method, in order to solve the prematurity and lower convergence speed in genetic algorithm(GA) for robotic path planning,a novel mobile robot path planning method based on ctuantum genetic algorithm(QGA) was proposed. This method uses grid method to establish mobile robot work environment model, artificial potential field to control mobile robot, quantum genetic algorithm to select the optimal or sub-optimal path, and double fitness evaluation function to evaluate the path to protect the optimal or sulroptimal path in to the next generation. The ability of finding the best solution and the stability of this method are greatly improved compared with GA and QGA by Simulation, and it has better convergent property and ability of searching more extensive space. It is fit for the solution of complex optmization problems.

Key words: Quantum genetic algorithm, Path planning, Robot, Artificial potential field, Grid