Paper
1 December 2023 Robot obstacle avoidance path planning based on improved artificial potential field
Lingyun Zhu, Hailong Xie, Ziyang Song
Author Affiliations +
Proceedings Volume 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023); 1294024 (2023) https://doi.org/10.1117/12.3010870
Event: Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 2023, Sipsongpanna, China
Abstract
In the realm of intelligent agent control, path planning has been one of the most well-liked study subjects. The path planning for obstacle avoidance approach proposed in this study is an enhanced artificial potential field method. By directing the barrier in the robot's direction and combining the boundary repulsion and vector decomposition of the goal direction, the local minimum problem is resolved. Next, the final combined force is delivered to the robot's center and the angle coefficient is added to provide a fair obstacle avoidance effect while taking into account the physical distance between the two sides of the robot and the quantity of extra environmental obstacles. Finally, the enhanced algorithm is used to perform a global path search. The simulation results validate the applicability and effectiveness of the suggested approach.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Lingyun Zhu, Hailong Xie, and Ziyang Song "Robot obstacle avoidance path planning based on improved artificial potential field", Proc. SPIE 12940, Third International Conference on Control and Intelligent Robotics (ICCIR 2023), 1294024 (1 December 2023); https://doi.org/10.1117/12.3010870
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Design and modelling

Mathematical optimization

Robot vision

Superposition

Unmanned aerial vehicles

Virtual reality

Visibility

Back to Top