Research on Obstacle Avoidance Algorithm of Fixed-wing UAV Swarms Based on Improved Artificial Potential Field

Qiping Zhou, Yong Wei, Wei He, Shu-min Shang, Haibo Fan, Weisong Yin
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引用次数: 1

Abstract

In the swarm formation control system by leader-follower strategy, obstacle avoidance is the key requirement of unmanned aerial vehicle (UAV) swarm to coordinate trajectory planning, while the traditional artificial potential field (APF) ignores the problem that the UAV swarm needs to return to the scheduled route immediately after obstacle avoidance. Based on the UAV obstacle avoidance rules, this paper proposes a trajectory planning scheme based on improved artificial potential field (IAPF). Though IAPF, the UAV swarm considers the minimum turning radius factor when avoiding obstacles, does not deviate from the route after obstacle avoidance, and returns to the scheduled route nearby, thus the unity of UAV swarm obstacle avoidance and trajectory planning is realized. The simulation results show that the proposed scheme can effectively solve the problem of UAV swarm returning to the scheduled route immediately after obstacle avoidance.
基于改进人工势场的固定翼无人机群避障算法研究
在leader-follower编队控制系统中,避障是无人机群协调轨迹规划的关键要求,而传统的人工势场(artificial potential field, APF)算法忽略了避障后无人机群需要立即返回预定路线的问题。基于无人机避障规则,提出了一种基于改进人工势场(IAPF)的轨迹规划方案。通过IAPF,无人机群在避障时考虑转弯半径因子最小,避障后不偏离路线,并在附近返回预定路线,实现了无人机群避障与轨迹规划的统一。仿真结果表明,该方案能有效解决无人机群避障后立即返回预定航线的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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