Supervisor:
Southwest Ordnance Industry Bureau
Organizer:
Chongqing Ordnance Industry Society
Chongqing University of Technology
Chongqing University of Technology
A collaborative search attack algorithm for multiple UAVs in mountain environments
| DOI: | 10.11809/bqzbgcxb2025.03.021 |
| Keywords: | multi UAV; mountain environment; collaborative search and attack; ant colony optimization; vector field histogram |
| Abstract: | In order to cope with the problem of multi UAV cooperative search and attack on unknown targets in the environment with irregular mountainous obstacles, an intelligent self organizing cooperative search attack algorithm for UAV swarm (IACO VFH) based on ant colony optimization algorithm (ACO) and vector histogram method (VFH) is designed. Firstly, a collaborative search attack optimization model is established with the goal of maximizing the search efficiency and the number of attacks. Secondly, in the process of cooperative search, VFH method is used to calculate the cost function, and then improve the heuristic function in the ACO algorithm using the cost function to enhance the obstacle avoidance performance of the UAV. Then, the pheromone diffusion update and dynamic increment factor are used to improve the pheromone update mechanism in the ACO algorithm, effectively balancing search coverage while improving local obstacle avoidance performance. Finally, the simulation results show that in a simple circular obstacle environment, the IACO VFH algorithm achieves an average coverage rate and average number of targets destroyed that are 11.79% and 2.46 targets higher, respectively, compared to the particle swarm optimization. At the same time, in the irregular mountainous terrain, the IACO VFH algorithm can effectively search for unknown static and dynamic targets in the battlefield environment while ensuring the flight safety of the UAV. |
| Issue: | Vol. 46 No. 3 (2025) |
| Published: | 2025-03-31 |