Improved Optimization Algorithm for Mobile Robot Path Planning

The current research related robot path planning methods exists local optimum,an improved mobile robot path planning algorithm is proposed,which uses novel artificial potential field to produce initialization population,and improved genetic algorithm introduces novel adaptive functions and flip mutation to optimize the global path.The adaptive functions include fitness of the path points and the path,increase evaluation performance,the flip mutation changes obstacle path into free path and makes the robot bypass smoothly obatacles.This method increases greatly the efficiency of the algorithm and overcomes the problem of premature convergence of the smiple genetic algorithm.Experimental results show the feasibility and effectiveness of the algorithm in path planning for mobile robot.