Sequential Single-Cluster Auctions for Robot Task Allocation

Multi-robot task allocation research has focused on sequential single-item auctions and various extensions as quick methods for allocating tasks to robots with small overall team costs. In this paper we outline the benefits of grouping tasks with positive synergies together and auctioning clusters of tasks rather than individual tasks. We show that with task-clustering the winner determination costs remain the same as sequential single-item auctions and that auctioning task-clusters can result in overall smaller team costs.