Trajectory planning for distributed multi-UAVs based on improved DWA
dechao wang, shengchun wang, qing cheng, yi ai · 2025
In response to the autonomous obstacle avoidance problem of multiple unmanned aerial vehicles under the influence of static and dynamic obstacles in complex operating environments, an optimized dynamic window method based on avoidance responsibility is proposed. Firstly, based on different types of conflicts, a new principle for dividing the collision zone of unmanned aerial vehicles is proposed, which refines the relief strategies and means adopted when encountering different conflicts. Secondly, based on the principle of conflict resolution and obstacle avoidance, a new responsibility evaluation function was designed to restrict and constrain specific drone conflict resolution actions. Finally, based on Matrix Laboratory (MATLAB) simulation verification, the improved optimization algorithm can effectively improve efficiency of trajectory planning and the success rate, especially when dealing with left and right-side conflicts. The planned path length was shortened by 6.6% and 26% respectively, and the planning time was reduced by 5.8% and 10% respectively, further verifying the superiority of the improved algorithm and effectively avoiding the local optimal path problem caused by unreasonable avoidance.