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

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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 paper 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.

Huan Liu, Xiamiao Li, Mingfeng Fan, Guohua Wu, Witold Pedrycz, Ponnuthurai Nagaratnam Suganthan• 2020

Related benchmarks

TaskDatasetResultRank
Static Path PlanningShort Map (C1-C4)
Path Length495.3
23
Static Path PlanningSparse Map (C9-C12)
Path Length515.3
23
Static Path PlanningLarge Map (C5-C8)
Path Length1.06e+3
23
Dynamic Path PlanningDynamic Scenarios Short Map Type
Path Length491.1
17
Dynamic Path PlanningDynamic Scenarios Sparse Map Type
Path Length489.4
17
Dynamic Path PlanningDynamic Scenarios Large Map Type
Path Length994.5
16
Dynamic Path PlanningDynamic Scenarios Dense Map Type
Path Length505.1
5
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