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arXiv:2002.10623 (cs)
[Submitted on 25 Feb 2020 (v1), last revised 8 Feb 2021 (this version, v2)]

Title:Feasible Computationally Efficient Path Planning for UAV Collision Avoidance

Authors:Han Wang, Muqing Cao, Hao Jiang, Lihua Xie
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Abstract:This paper presents a robust computationally efficient real-time collision avoidance algorithm for Unmanned Aerial Vehicle (UAV), namely Memory-based Wall Following-Artificial Potential Field (MWF-APF) method. The new algorithm switches between Wall-Following Method (WFM) and Artificial Potential Field method (APF) with improved situation awareness capability. Historical trajectory is taken into account to avoid repetitive wrong decision. Furthermore, it can be effectively applied to platform with low computing capability. As an example, a quad-rotor equipped with limited number of Time-of-Flight (TOF) rangefinders is adopted to validate the effectiveness and efficiency of this algorithm. Both software simulation and physical flight test have been conducted to demonstrate the capability of the MWF-APF method in complex scenarios.
Comments: IEEE International Conference on Control and Automation (ICCA) 2018
Subjects: Robotics (cs.RO)
Cite as: arXiv:2002.10623 [cs.RO]
  (or arXiv:2002.10623v2 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2002.10623
Journal reference: 2018 IEEE International Conference on Control and Automation (ICCA)
Related DOI: https://doi.org/10.1109/ICCA.2018.8444284

Submission history

From: Han Wang [view email]
[v1] Tue, 25 Feb 2020 02:02:26 UTC (1,558 KB)
[v2] Mon, 8 Feb 2021 13:52:28 UTC (1,558 KB)
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