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 echofix spring reverb 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 bilstein shocks jeep xj 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.