Dynamic Trajectory Planning for UAV in Complex Environments

To address the problem of poor obstacle avoidance ability of UAV in complex dynamic environment, a dynamic trajectory planning algorithm is proposed for Unmanned Aerial Vehicles (UAVs), which integrates the Dynamic Window Approach (DWA) and Particle Swarm Optimization (PSO). To obtain the optimal trajectory for UAVs in static environments, a parameterized flight trajectory representation method is employed, and PSO is utilized for nominal trajectory planning to enhance the solution efficiency. By leveraging the globally optimal trajectory, a trajectory evaluation function is established, and guidance commands are generated using DWA to avoid dynamic obstacles. Simulation results demonstrate that the proposed dynamic trajectory planning algorithm effectively balances the requirements of limited computing ability, shortest flight trajectory and real-time obstacle avoidance.