Path Planning based on Artificial Potential Field with Particle Swarm Optimization
Li Cao, Ping Xu · 2025
The artificial potential field method is commonly utilized in path planning, with its basic idea resembling an electromagnetic field. However, traditional artificial potential field methods suffer from issues such as unreachable targets and easily falling into local minima. To address these limitations, this paper proposes an enhanced artificial potential field method. It proposes an improved repulsive potential field function, which effectively resolves the problem of unreachable targets, and incorporates a road potential field, significantly enhancing the practicality of the algorithm. A fused particle swarm artificial potential field method is proposed, which solves the local optimum problem and improves the search efficiency. The proposed algorithm is subsequently validated using MATLAB, and the experimental results demonstrate that it effectively addresses the aforementioned challenges and plans a collision - free, safe path.