TIG*: Enhanced Tangent Intersection Guidance for Efficient 3D UAV Path Planning in Complex Environments

Navigating unmanned aerial vehicles (UAVs) efficiently and safely in complex 3D environments, especially those with unknown maps, remains a significant challenge for general autonomous applications. This paper introduces TIG*, an improved version of the Tangent Intersection Guidance algorithm designed to address this challenge by generating shorter and smoother paths with minimal computational time in environments with irregular shapes. TIG* operates by identifying obstacles and selecting optimal avoidance tangents using an optimized heuristic cost function. The evaluations in static environments show that TIG* outperforms static 3D-TG, PRM*, RRT*, and Informed RRT* across key metrics, including path length, smoothness, algorithm success, and computational time. In many cases, TIG* is capable of generating paths in less than 0.05 seconds, making it highly suitable for efficient pre-mission planning in diverse mission scenarios. Furthermore, for online scenarios, the proposed O-TIG* algorithm offers real-time adaptability, smoothly modifying paths in response to unforeseen obstacles. Comparative studies show that O-TIG* requires fewer path modifications, faster re-planning, and superior smoothness compared to dynamic 3D-TG, RH-RRT* and APF, even in dense clutter, which is crucial for UAV survivability and mission continuity in dense settings. TIG* represents a powerful and practical solution by integrating the geometric solution with optimized path calculation for next-generation UAV navigation, particularly for demanding and critical missions.