A novel multi-UAV patrol path planning method based on evolutionary multi-objective optimization
Longmei Li, Shuai Zhou, Zheng Wang · 2022
This paper investigates collaborate path planning of multiple Unmanned Aerial Vehicles (UAVs) for area patrolling. The problem includes task assignment and path planning for each UAV in the team. In the scenario of urgent observation, two objectives are considered simultaneously, i.e., time cost and energy cost. The problem is formulated as a multiple traveling salesman problem (MTSP) with multiple depots, which is a nondeterministic polynomial-hard problem. A decompositionbased multi-objective algorithm with 2-opt local search strategy is proposed to solve the problem. Through computational experiments, the benefit of the novel algorithm (MOEA/D-2opt) is demonstrated by comparing with other existing algorithms. Experimental results show that proposed algorithm is effective and efficient in solving the multi-UAV patrol path planning problem.