An Improved Trajectory Planning Method for Unmanned Aerial Vehicles in Complex Environments

Trajectory planning plays a crucial role in the execution of Unmanned aerial vehicle (UAV) missions. However, planning an optimal collision-free trajectory is a challenging task, especially in complex environments. To address the above issue, an enhanced Elliptical tangent graph algorithm (ETG-CPI) based on comprehensive performance indicator is proposed in the present study. In the proposed algorithm, the comprehensive performance indicator, which contains the obstacle avoidance frequency, the yaw angle and the distance from the start point to the candidate waypoint, is used to select promising waypoints. Moreover, the entropy weight method is used to integrate these performance indicators. The experimental results demonstrate that the proposed algorithm outperforms four competitive path planning methods in 26 different environments. Additionally, the results indicate that the proposed comprehensive path evaluation method can help the proposed algorithm find a high-quality path in complex environments.