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Published on 25 September 2023
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Lu,X. (2023). Improved path planning method for unmanned aerial vehicles based on artificial potential field. Applied and Computational Engineering,10,64-71.
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Improved path planning method for unmanned aerial vehicles based on artificial potential field

Xinyi Lu *,1,
  • 1 Northeastern University at Qinhuangdao

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/10/20230142

Abstract

With the advancement of unmanned aerial vehicle (UAV) technology and its widespread use in many facets of manufacturing and daily life, the need for UAV mission automation is becoming more and more practical. In order to improve the automatic obstacle avoidance and path planning performance of UAVs, this essay proposes an optimized route planning algorithm based on the artificial potential field (APF) method, which have solved the typical issue of the APF. This method chooses to conduct a pre planning trajectory of the UAV based on a rapidly expanding random tree (RRT). The pre-planned path will be split into continuous particles, and then generating intermediate waypoints. A nearby waypoint offers a gravitational force to aid the UAV in escaping the local minimum when it enters it. At the same time, taking the distance from the UAV to the obstacle and the radius of influence of the obstacle itself into consideration, dynamically adjust the gravitational and repulsive coefficients, set up a non-gravitational zone around the obstacle, which is beneficial for the UAV to elude the obstacle. And set up a repulsive limited action zone to reduce unnecessary turns in the trajectory to achieve the effect of path optimization. Considering the difficulty of single UAV missions in most cases, this paper discusses cooperative flight path planning for multiple UAVs into consideration.

Keywords

unmanned aerial vehicle (UAV), route planning, artificial potential field (APF), rapidly expanding random tree (RRT).

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Cite this article

Lu,X. (2023). Improved path planning method for unmanned aerial vehicles based on artificial potential field. Applied and Computational Engineering,10,64-71.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Mechatronics and Smart Systems

Conference website: https://2023.confmss.org/
ISBN:978-1-83558-009-7(Print) / 978-1-83558-010-3(Online)
Conference date: 24 June 2023
Editor:Alan Wang, Seyed Ghaffar
Series: Applied and Computational Engineering
Volume number: Vol.10
ISSN:2755-2721(Print) / 2755-273X(Online)

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