Development of Optimal Strategies for Task Assignment in Multirobot Systems

Abstract

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. The problem is cast in the framework of multi-robot dynamic task allocation and then two methods are described that follow general guidelines for task allocation strategies. In the first method, four distinct task allocation strategies are considered using a simulated grid world. 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. In the second method, a multi-criteria assessment model capable of evaluating the suitability of individual robots is considered for a specified task according to their capabilities, and existing tasks. Candidates are ranked based on their suitability scores to support administrators in selecting appropriate robots to perform the tasks. The proposed assessment models overcome the lack of role-based task assignment in workflow management systems.