TIG算法让无人机在复杂环境中快速规划出最短、平滑的飞行路径。
Enhanced UAV Path Planning Using the Tangent Intersection Guidance (TIG) Algorithm
- 用椭圆切线交点法生成路径，分段优化选最优路线。
- 静态环境下路径最短，耗时低至0.01秒，转弯更少。
- 动态环境实时避障能力强，适合实战与救援场景。
无人机高效安全导航对作战支援、快递配送和搜救行动至关重要。本文提出一种新型路径规划算法——切线交点引导（TIG），适用于静态与动态环境。该算法基于椭圆切线交点法生成可行路径，对每个威胁区域生成两条子路径，依据启发式规则选择最优路线，并迭代优化直至抵达目标。结合无人机运动学与动力学约束，采用基于二次Bézier曲线的改进平滑技术，生成平滑高效的飞行轨迹。实验表明，在静态环境中，TIG算法生成最短路径，耗时低至0.01秒，相比A*、PRM、RRT*、Tangent Graph和Static APPATT算法，转弯角度更少；在完全未知与部分已知环境中，TIG展现出优异的实时避障能力，优于APF与Dynamic APPATT算法。
原文摘要 · Abstract (English)
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 Bézier 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.
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