Emergent Robot Differentiation in Distributed Multi-Robot Task Allocation

Abstract

1 Introduction and Motivation Multi-robot task allocation (MRTA) algorithms for heterogeneous groups ofrobots have to be able to differentiate between robots based on their performance in order to optimize allocation. Existing MRTA algorithms [?,?] gener-ally do this based on hand-coded information about the task utilities relative to each robot. Using hand-coded task utilities, however, these algorithms aretypically not sensitive to the effects of group dynamics, such as interference and synergy. These effects typically have to be estimated at runtime as theyare difficult to model due to their volatility and complexity.