Dynamic Path Planning for Mobile Robot Based on Improved Genetic Algorithm

The paper proposes the dynamic path planning method of mobile robot based on improved genetic algorithm. Firstly, to ensure the safety of the robot effectively, the improved visual graph and the conception of safety coefficient are presented. Secondly, to avoid the local optimum, the paper replaces the mutation individual with a better individual searched by hill-climbing method. To increase the convergence speed, the paper updates the colony by the rule of the particle swarm optimization. Thirdly, float-point coding is proposed in the improved genetic algorithm. The fitness function includes the length and the total slope of the path in dynamic path planning. Finally, it emulates the dynamic path planning for mobile robot based on improved genetic algorithm. From the results, it can see that the path planning method is viable and efficient.