Abstract:

The task allocation was studied based on the swarm inteeligence for the large-scale multi-robot system with looseand tightcoupled tasks adopting the hierarchial architecture. In the high level, the ant colony algorithm was employed to find the optimal allocation of the loosecoupled tasks, namely, based on the reverse distribution idea,taking each ant to form a task, an undertaker was chosen for every task. In the low level,the coalition formation algorithms based on the ant colony optimization(ACO),the particle swarm and ant colomy optimization(PSACO),or the quantuminspised ant colony optimization(QACO) was proposed respectively for performin a tight-coupled task.Simulations were performed and results showed that PSACO provides the best solution,but its running time is the largest;QACO is a little inferior in solution quality to PSACO, however,it needs only a half time of the 2 other methods. Therefore, QACO appears more suitable for the task allocation of the large-scale multi-robot system.

Key words: automatic control technology, task allocation, robot coalition formation, ant colony optimization, particle swarm and ant colony optimization, quantum-inspired ant colony optimization