Abstract
Nowadays, robots are faced with real-time, dynamic, complex and confrontational working environment. It is significant to analyze task allocation in multi-robot systems. In this paper, a dynamic auction approach for differentiated tasks under cost rigidities (DAACR) is proposed, which can obtain optimal results in the task allocation of rescue robots. To verify the feasibility of the proposed approach, we investigate the optimality of the DAACR and compare it with other task allocation approaches based on the Hungarian algorithm. The results show that robots using this algorithm can adapt to a variety of complicated work environments, accomplish more tasks in limited time, reduce the delay of task allocation, and improve the overall utility of multi-robot systems.
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