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

TL;DR

This paper presents the Tangent Intersection Guidance (TIG) algorithm for UAV path planning, demonstrating improved efficiency, safety, and real-time adaptability in static and dynamic environments compared to existing methods.

Contribution

The paper introduces the TIG algorithm, combining elliptic tangent intersection paths with a smoothing technique, advancing UAV navigation in complex environments.

Findings

Generates shortest paths in 0.01 seconds

Fewer turning angles than existing algorithms

Effective in unknown and partially known environments

Abstract

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.