Global Dynamic Path Planning Algorithm Based on Harmony Search Algorithm and Artificial Potential Field Method

For public places with complex environment and many dynamic obstacles, a dynamic path planning method combining global and local planning is proposed in this paper. Firstly, the mathematical model is established, and solved by harmony search algorithm. Secondly, optimization is performed by opposition-based learning and optimal learning, and the extraction rate of the harmony memory is dynamically adjusted. Finally, by combining the artificial potential field method and adding local target points, a global dynamic path planning algorithm considering the global path optimization and real-time obstacle avoidance performance is constructed. Experiments show that the algorithm has more advantages in path length and smoothness, and can avoid dynamic obstacles.