A fast and frugal method for team-task allocation in a multi-robot transportation system

Abstract

In this paper we present two task-allocation strategies for a multi-robot transportation system. The first strategy is based on a centralized planner that uses domain knowledge to solve the assignment problem in linear time. In contrast in the second strategy, individual robots make rule-based allocation decisions using only locally obtainable information and single value communication. Both methods are tested and analysed in simulation experiments. We show that the rule-based method performs well but the lack of information has to be paid for with increased energy consumption.