Volume 38, Number 5, October 2020
|Page(s)||977 - 986|
|Published online||08 December 2020|
3D Path Planning Method for UAV Based on Improved Artificial Potential Field
School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
Path planning is the key technology for UAV to achieve autonomous flight. Considering the shortcomings of path planning based on the conventional potential field method, this paper proposes an improved optimization algorithm based on the artificial potential field method and extends it to three-dimensional space to better achieve flight constrained 3D online path planning for UAVs. The algorithm is improved and optimized aiming at the three problems of goal nonreachable with obstacle nearby (GNWON), easy to fall into local minimum, and path oscillation in traditional artificial potential field method. First, an improved potential field function with relative distance is used to solve the GNWON, and an optimized repulsive potential field calculation method based on different obstacles or threat models is proposed to optimize the planned path. Secondly, in order to make the drone jump out of the local minimum trap, a method of setting heuristic sub-target points is proposed. For local path oscillation, a method using memory sum force was proposed to improve the oscillation. The simulation results show that the improved optimization algorithm in this paper effectively makes up for the shortcomings of the traditional artificial potential field method, and the designed 3D online path planning algorithm for the UAV is practical and feasible.
Key words: unmanned aerial vehicle (UAV) / path planning / artificial potential field / heuristic sub-target / memory force / optimization algorithm / simulation
关键字 : 无人机 / 路径规划 / 人工势场法 / 启发式子目标点 / 记忆合力
© 2020 Journal of Northwestern Polytechnical University. All rights reserved.
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