Shape control of cyclic networks in multi-robot formations

Abstract

This paper addresses coalition formation, based on agent capabilities, centered on task allocation in emergency-response environments (EREs). EREs are environments that need fast task completion as their main requirement. We propose a team-based organization model, based on an existing organization model for adaptive complex systems. The model has some key characteristics that are beneficial for EREs: agents act in dynamic, open domains; agents collaborate in completing group tasks; agents may have similar types of capabilities, but at different levels; tasks need different agent capabilities, at collective different levels; and agents are supervised in a partially decentralized manner. We formulate task allocation as a capability-based coalition-formation problem, propose a greedy myopic algorithm to form coalitions, and compare it with F-Max-Sum, another efficient myopic algorithm. Experiments in which utility is measured show that the capability-based approach outperforms the role-based one. The numerical experiments suggest that the proposed task allocation method is possibly scalable with growing numbers of agents.