A comprehensive taxonomy for multi-robot task allocation

Task allocation is an important aspect of many multi-robot systems. The features and complexity of multi-robot task allocation (MRTA) problems are dictated by the requirements of the particular domain under consideration. These problems can range from those involving instantaneous distribution of simple, independent tasks among members of a homogenous team, to those requiring the time-extended scheduling of complex interrelated multi-step tasks for a members of a heterogenous team related by several constraints. The existing widely-used taxonomy for task allocation in multi-robot systems addresses only problems with independent tasks and does not deal with problems with interrelated utilities and constraints. A survey of recent work in multi-robot task allocation reveals that this is a significant deficiency with respect to realistic multi-robot task allocation problems. Thus, in this paper, we present a new, comprehensive taxonomy, iTax, that explicitly takes into consideration the issues of interrelated utilities and constraints. Our taxonomy maps categories of MRTA problems to existing mathematical models from combinatorial optimization and operations research, and hence draws important parallels between robotics and these fields.