In view of the shortcomings of traditional path planning methods,such as excessive dependence on environmental prior information,weak real-time performance of path planning and difficulty in adapting to complex obstacle environment,an improved Dynamic Window Approach (DWA) based on the theory of electric potential energy is proposed to expand the subfunction space of trajectory evaluation.Firstly,the design of predictive trajectory selection function is improved to guide the jump out of local optimum and get away from the concave obstacle environment.At the same time,the dynamic adjustment mechanism of the weight of the velocity evaluation function is designed to enhance the ability to cross dense obstacle areas.Finally,the design of target navigation function is added to improve the guidance ability of the algorithm towards the target point.Simulation experiments show that the improved algorithm can effectively overcome the problems of traditional DWA algorithm,such as prone to fall into local optimum and unable to deal with complex obstacles,and effectively improve the path planning ability and real-time performance of the algorithm.