Cooperative Task Allocation for Multi-UAV Systems Based on ACO, A* and DWA

This paper addresses the efficient cooperative task allocation of multiple unmanned aerial vehicles (UAVs) using a hybrid algorithm based on the Ant Colony System, integrating the A* algorithms and the Dynamic Window Approach to avoid fixed and moving obstacles, respectively. The research highlights the importance of efficient coordination in missions with multiple collaborative robots, emphasizing the need to integrate navigation and sensing to avoid collisions and plan routes efficiently. A mathematical model is proposed, considering various constraints, such as the UAVs maximum travel distance and reward collection capacity. Finally, the proposed algorithm proves to be effective in planning routes in complex scenarios, can be used to analyze the feasibility of carrying out missions and can indicate the ideal number of UAVs.