关键词: 多机器人, 救火任务, 任务分配, 合同网, 帕累托改进, 帕累托最优

Abstract: In order to solve the optimization problem of dynamic task allocation in multi-robot system, a new quadratic task allocation algorithm based on Pareto improvement was proposed based on the initial task allocation of contract net. When the fire fighting task was performed by the multi-robot system in parallel, firstly, the multiple robots were divided into several sub-group through the initialization of task allocation. Then, a fire fighting task was undertook by a subgroup, and the robots needed to be migrated were determined by the Pareto improvement of the subgroup and its nearest subgroup while the subgroup performing the task to achieve the Pareto optimality between the two subgroups. Finally, the global Pareto optimality was achieved by the Pareto improvement of all subgroups with posterior binary tree traversal. The theoretical analysis and simulation results show that, compared with reinforcement learning algorithm and ant colony algorithm, the fire fighting time of the proposed algorithm is reduced by 26.18% and 37.04% respectively. And compared with the traditional contract net method, the proposed algorithm can perform the fire fighting task efficiently in time, and also has the obvious advantage in system revenue.

Key words: multi-robot, fire fighting task, task allocation, contract net, Pareto improvement, Pareto optimality