Research on multi-UAV autonomous obstacle avoidance algorithm integrating improved dynamic window approach and ORCA.

To address the issue that traditional UAV obstacle-avoidance algorithms had low efficiency in unknown and complex environments, an improved DWA (Dynamic Window Approach) fusion algorithm was proposed. Regarding the lack of a global perspective in the DWA algorithm, a bidirectional search strategy was introduced to enhance the global value of the planned trajectory. Confronted with the difficulty of balancing calculation speed and accuracy in the DWA algorithm, a dynamic time step adjusted according to the environment was designed to weigh the computational efficiency. Aiming at the poor environmental adaptability of the DWA algorithm, a trajectory evaluation function with variable weights was put forward to improve environmental fitness. To boost the inter-UAV obstacle-avoidance ability in the multi-UAV collaborative mode, the improved DWA algorithm was integrated with the Optimal Reciprocal Collision Avoidance (ORCA) method. Simulation experiments were conducted to verify the effectiveness of the proposed improved fusion algorithm. Compared with the conventional DWA algorithm, the proposed method achieved a 27.90% reduction in UAV flight path length, a 17.01% decrease in mission completion time, and a 21.5% reduction in iteration counts. These significant performance improvements demonstrated its practical value for engineering applications of multi-UAV autonomous obstacle-avoidance technology.