Abstract: Aiming at the problem of multi\|unmanned aerial vehicle (multi-UAV) task allocation, we proposed a multi-UAV task assignment method based on adaptive salps swarm algorithm. On the basis of the classic salps swarm algorithm, the leader’s position updating formula was redesigned to improve the defect that salps swarm algorithm was easy to fall into local optimality. At the same time, adaptive operators were added during  iterative process of the algorithm to dynamically adjust the number of leaders and followers, so as  to improve the global search  in the early stage and the ability to jump out of local extremes in the later stage. Through the comparative experiments with genetic algorithm, particle swarm optimization algorithm and the classical salps swarm algorithm, the experimental results show that the proposed algorithm has better effect on solving the problem of multi-UAV task assignment, and has better adaptability and convergence.

Key words: multi-unmanned aerial vehicle, task assignment, adaptive salps swarm algorithm, genetic algorithm