arXiv 2208.031172024-04-23cs.RO

基于人工势场的动态环境中固定翼无人机避障算法的重新表述

A reformulation of collision avoidance algorithm based on artificial potential fields for fixed-wing UAVs in a dynamic environment

Delhi Technological University（德里理工大学）；Indian Institute of Science, Education, and Research, Bhopal（印度科学教育与研究学院博帕尔分校）

Astik Srivastava, P. B. Sujit

备注：: This paper presents a preliminary work and is not intended for publication. Correction: There was a typo in equation 8 of this paper that has been corrected. Still, it is advised to kindly refer the updated version of this article available here for pdf (https://www.researchgate.net/publication/371878158_A_Modified_Artificial_Potential_Field_for_UAV_Collision_Avoidance)

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AI总结：

本文针对固定翼无人机无法遵循停止-决策-执行方法的问题，提出了一种基于人工势场改进斥力定义的反应式避障算法，并通过多场景仿真验证了其在动态环境中的可行性与安全性。

摘要：

随着小型无人机在民用领域的日益普及，它们在杂乱环境中安全运行的方法需求不断增长，特别是对于无法遵循停止-决策-执行方法的固定翼无人机。本文提出了初步研究，设计了一种基于人工势场算法中改进斥力定义的反应式避障算法，以实现固定翼无人机在杂乱、动态环境中的可行且安全的导航。我们展示了改进定义在多种场景下的仿真结果，并讨论了未来可能的研究方向以改进这些结果。

英文摘要：

As mini UAVs become increasingly useful in the civilian work domain, the need for a method for them to operate safely in a cluttered environment is growing, especially for fixed-wing UAVs as they are incapable of following the stop-decide-execute methodology. This paper presents preliminary research to design a reactive collision avoidance algorithm based on the improved definition of the repulsive forces used in the Artificial potential field algorithms to allow feasible and safe navigation of fixed-wing UAVs in cluttered, dynamic environments. We present simulation results of the improved definition in multiple scenarios, and we have also discussed possible future studies to improve upon these results.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。