Path Planning Using Artificial Potential Field Method And A-star Fusion Algorithm
Chunyu Ju, Qinghua Luo, Xiaozhen Yan
Abstract
Aiming at the deficiencies in A-star algorithm and artificial potential field method, this paper proposes a fusion algorithm based on artificial potential field method and A-star algorithm. Although the A-star algorithm can obtain a relatively short path, it cannot handle dynamic obstacles, the artificial potential field method can handle dynamic obstacles but the generated path is much longer than the A-star algorithm. Artificial potential field method and A-star fusion algorithm is proposed to avoid dynamic obstacles and find a shorter path simultaneously. Then we evaluated our proposed method by comparing it with the A-star algorithm, artificial potential field method and two other reference methods. The simulation results show that our proposed method can generate a shorter path and effectively avoid dynamic obstacles.