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Enhanced UAV Path Planning Using the Tangent Intersection Guidance (TIG) Algorithm

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Efficient and safe navigation of Unmanned Aerial Vehicles (UAVs) is critical for various applications, including combat support, package delivery and Search and Rescue Operations. This paper introduces the Tangent Intersection Guidance (TIG) algorithm, an advanced approach for UAV path planning in both static and dynamic environments. The algorithm uses the elliptic tangent intersection method to generate feasible paths. It generates two sub-paths for each threat, selects the optimal route based on a heuristic rule, and iteratively refines the path until the target is reached. Considering the UAV kinematic and dynamic constraints, a modified smoothing technique based on quadratic B\'ezier curves is adopted to generate a smooth and efficient route. Experimental results show that the TIG algorithm can generate the shortest path in less time, starting from 0.01 seconds, with fewer turning angles compared to A*, PRM, RRT*, Tangent Graph, and Static APPATT algorithms in static environments. Furthermore, in completely unknown and partially known environments, TIG demonstrates efficient real-time path planning capabilities for collision avoidance, outperforming APF and Dynamic APPATT algorithms.

Hichem Cheriet, Khellat Kihel Badra, Chouraqui Samira• 2025

Related benchmarks

TaskDatasetResultRank
Static Path PlanningShort Map (C1-C4)
Path Length493.8
23
Static Path PlanningLarge Map (C5-C8)
Path Length1.00e+3
23
Static Path PlanningSparse Map (C9-C12)
Path Length511.6
23
Static Path PlanningDense Map (C13-C16)
Path Length509.8
20
Dynamic Path PlanningDynamic Scenarios Short Map Type
Path Length485.9
17
Dynamic Path PlanningDynamic Scenarios Sparse Map Type
Path Length489
17
Dynamic Path PlanningDynamic Scenarios Large Map Type
Path Length990.6
16
Dynamic Path PlanningDynamic Scenarios Dense Map Type
Path Length505.4
5
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