A combined path planning algorithm based on artificial potential field algorithm and A* algorithm

Zengxu Song; Zuoxun Wang Sr.; Shuai Zhang; Jixiang Yan

doi:10.1117/12.2640276

1 August 2022 A combined path planning algorithm based on artificial potential field algorithm and A* algorithm

Zengxu Song, Zuoxun Wang Sr., Shuai Zhang, Jixiang Yan

Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 122571K (2022) https://doi.org/10.1117/12.2640276
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China

Abstract

In order to ensure that mobile robots perform various tasks correctly, the research on efficient and practical path planning algorithms is of great significance. For the Artificial Potential Field algorithm, it is easy to fall into local minimums, the target points are unreachable, and the A* algorithm search time is long when planning the moving path. The speed is slow, the planned path is not smooth enough and it is not the optimal path. This paper proposes a mobile robot combined path planning algorithm based on the APF algorithm and the A* algorithm. This algorithm can solve the local oscillation problem while reducing the problem. Obstacle avoidance time, improve the efficiency of the navigation algorithm. From the results of MATLAB Simulation, it can be seen that the algorithm can complete path planning accurately and efficiently. The mobile robot can bypass the local minimum point and successfully reach the target point, achieving the expected path planning effect.

Citation Download Citation

Zengxu Song, Zuoxun Wang Sr., Shuai Zhang, and Jixiang Yan "A combined path planning algorithm based on artificial potential field algorithm and A* algorithm", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 122571K (1 August 2022); https://doi.org/10.1117/12.2640276

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available