Task apportionment in a rearrangement problem of multiple mobile robots

Abstract A rearrangement problem involving multiple mobile robots is addressed in this paper. In the problem, it is important to identify task decomposition, task allocation, and path planning applicable to distinct environments while rearrangement tasks are executed. We here define ‘task apportionment’ as an operation that sets up task decomposition and conducts task allocation based on that setup. We propose a method for task apportionment and path planning applicable to distinct environments. The method establishes the necessary intermediate configurations of objects as one way of task decomposition and determines task allocation and path planning as a semi-optimized solution by using simulated annealing. The proposed method is compared with a continuous transportation method and a territorial method through simulations and experiments. In the simulations, the proposed method is, on the average, 17 and 20% faster than the continuous transportation method and the territorial method, respectively. In the experiments, the proposed method is, on the average, 22 and 16% faster than the continuous transportation and the territorial method, respectively. These results show that the proposed method can realize an efficient rearrangement task by mobile robots in various working environments under feasible computation time, especially in environments with a mixture of wide and narrow areas and an uneven distribution of objects.