New improvement of "dynamic repulsive potential factor" on artificial potential field path planning algorithm

Dapeng Wang

doi:10.1117/12.2622875

1 December 2021 New improvement of "dynamic repulsive potential factor" on artificial potential field path planning algorithm

Dapeng Wang

Author Affiliations +

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120790Q (2021) https://doi.org/10.1117/12.2622875
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

Path-planning as one of the most fundamental tasks of robots should cause less burden on calculation capacity and be efficient when the robots’ major tasks are not only about motion. Artificial Potential Field (APF) algorithm as an effective and simple path-planning method could meet such a requirement. However, the local minimum problem limits its application on robot’s path-planning tasks. To deal with this problem, this paper proposed a method named “Dynamic Repulsive Potential Factor” (DRPF). Compared to other existed improvements such as the sub-target strategy and combination algorithms with Rapidly exploring Random Tree (RRT), DRPF has the advantages of simple and effective. And the produced path of DRPF is shorter than the one produced by APF combing RRT, which is demonstrated in the experiment result. Meanwhile, the robot is continuing to move in the DRPF method while it is stopped when searching path in RRT, demonstrating the effectiveness on time aspect. The application of DRPF could meet the requirements of efficient and less calculation burden for path-planning function of robots whose major tasks are not only about navigation.

Citation Download Citation

Dapeng Wang "New improvement of "dynamic repulsive potential factor" on artificial potential field path planning algorithm", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120790Q (1 December 2021); https://doi.org/10.1117/12.2622875

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