Multiple-UAV Path Planning in Obstacle Environments with Evolutionary Computation
Bui Trong Dung, Trinh Van Chien, Van Son Nguyen, Minh Trong Hoang, Phuong Nhung Do, Hoang Anh Dang · International Journal of Computers Communications & Control · 2025
Broadcasting to various devices is a critical requirement when applying 5G and B5G networks. Unmanned aerial vehicles (UAVs) are expected to facilitate wireless 5G connection to remote areas with high data transmission speed. However, optimizing the flight paths of multiple UAVs is a significant challenge. The primary concerns include ensuring the UAVs avoid collisions with each other and with obstacles in the flying environment while maintaining efficient end-to-end routes. To address the challenge, this research proposes effective multiple-UAV route planning techniques. Two multiple-UAV approaches based on genetic algorithm (GA) and particle swarm optimization (PSO) are utilized in this paper. In complex scenarios, the proposed methods effectively determine the optimal UAV routes while satisfying various constraints. Simulation results indicate that GA is faster to output final paths but PSO has better flight paths.