Cooperative Task Planning of Multi-Robot System

Multiple cooperating robots hold the promise of improved performance and increased fault tolerance for large-scale problems. A robot team can accomplish a given task more quickly than a single agent by executing them concurrently. A team can also make effective use of specialists designed for a single purpose rather than requiring that a single robot be a generalist. Multi-robot coordination, however, is a complex problem. An empirical study is described in the present paper that sought general guidelines for task allocation strategies. Different task allocation strategies are identified, and demonstrated in the multi-robot environment. A simulation study of the methodology is carried out in a simulated grid world. The results show that there is no single strategy that produces best performance in all cases, and that the best task allocation strategy changes as a function of the noise in the system. This result is significant, and shows the need for further investigation of task allocation strategies.