Scalable Task Assignment for Heterogeneous Multi-Robot Teams

This work deals with the development of a dynamic task assignment strategy for heterogeneous multi‐robot teams in typical real world scenarios. The strategy must be efficiently scalable to support problems of increasing complexity with minimum designer intervention. To this end, we have selected a very simple auction‐based strategy, which has been implemented and analysed in a multi‐robot cleaning problem that requires strong coordination and dynamic complex subtask organization. We will show that the selection of a simple auction strategy provides a linear computational cost increase with the number of robots that make up the team and allows the solving of highly complex assignment problems in dynamic conditions by means of a hierarchical sub‐auction policy. To coordinate and control the team, a layered behaviour‐based architecture has been applied that allows the reusing of the auction‐based strategy to achieve different coordination levels.