Multi-Robot Task Allocation in Uncertain Environments

Multiple cooperating robots hold the promise of improved performance and increased fault tolerance for large-scale problems such as planetary survey and habitat construction. Multi-robot coordination, however, is a complex problem. We cast this problem in the framework of multi-robot dynamic task allocation under uncertainty. We then describe an empirical study that sought general guidelines for task allocation strategies in multi-robot systems. We identify four distinct task allocation strategies, and demonstrate them in two versions of the multi-robot emergency handling task. We describe an experimental setup to compare results obtained from a simulated grid world to those obtained from physical mobile robot experiments. Data resulting from eight hours of experiments with multiple mobile robots are compared to the trend identified in simulation. The data from the simulations 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 and their application to planetary exploration.