記憶ベース壁沿い走行と人工ポテンシャル法を組み合わせたUAV衝突回避の計算効率の良い経路計画
Feasible Computationally Efficient Path Planning for UAV Collision Avoidance
壁沿い走行法と人工ポテンシャル法を履歴軌跡の記憶で切り替え、低計算能力のドローンでもリアルタイムに衝突回避できるMWF-APF法を提案し、シミュレーションと実機飛行で有効性を示した。
著者: Han Wang, Muqing Cao, Hao Jiang, Lihua Xie
分類: cs.RO
原文アブストラクト
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.
