4.7 Article

An Autonomous Path Planning Method for Unmanned Aerial Vehicle Based on a Tangent Intersection and Target Guidance Strategy

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2020.3030444

关键词

Elliptic tangent graph; target guidance; UAV; path planning; obstacle avoidance

资金

  1. National Natural Science Foundation of China [62073341]
  2. Natural Science Fund for Distinguished Young Scholars of Hunan Province [2019JJ20026]
  3. National Natural Science Foundation of Hunan Province [2020JJ4748]

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This article proposes a novel autonomous path planning algorithm APPATT based on a tangent intersection and target guidance strategy. The algorithm can generate high-quality collision-free paths for UAVs in static and uncertain environments, with fast computation speed and adaptability.
Unmanned aerial vehicle (UAV) path planning enables UAVs to avoid obstacles and reach the target efficiently. To generate high-quality paths without obstacle collision for UAVs, this article proposes a novel autonomous path planning algorithm based on a tangent intersection and target guidance strategy (APPATT). Guided by a target, the elliptic tangent graph method is used to generate two sub-paths, one of which is selected based on heuristic rules when confronting an obstacle. The UAV flies along the selected sub-path and repeatedly adjusts its flight path to avoid obstacles through this way until the collision-free path extends to the target. Considering the UAV kinematic constraints, the cubic B-spline curve is employed to smooth the waypoints for obtaining a feasible path. Compared with A*, PRM, RRT and VFH, the experimental results show that APPATT can generate the shortest collision-free path within 0.05 seconds for each instance under static environments. Moreover, compared with VFH and RRTRW, APPATT can generate satisfactory collision-free paths under uncertain environments in a nearly real-time manner. It is worth noting that APPATT has the capability of escaping from simple traps within a reasonable time.

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