Tangent A* Planner: Enabling UAV Navigation in Obstacle-Rich Environments

Unmanned Aerial Vehicles (UAVs) have played a crucial role in various applications, from surveillance to package delivery in recent years. Effective path-planning algorithms are essential for ensuring safe and efficient navigation in environments cluttered with obstacles. This paper introduces a new path planning algorithm based on the traditional A* algorithm and tangent graph intersection, called the Tangent A* planner. Unlike the A* technique, and instead of getting neighbors using grids, the algorithm utilizes obstacles to calculate tangent lines, which are then considered as potential neighbors. Moreover, it employs the A* heuristic function to determine the optimal path. The paper evaluates the performance of Tangent A* compared with A*, PRM, and RRT<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> algorithms on randomly generated maps with elliptic obstacles. The experimental results show that our algorithm can generate the shortest collision-free path with fewer nodes, fewer turning angles, and the fastest motion time under static environments. These findings highlight the Tangent A* planner as a promising solution for UAV path planning in static environments, offering significant advantages in terms of speed, path quality, and smoothness.