Distributed and communication-aware coalition formation and task assignment in multi-robot systems

Abstract

In many missions, multiple robots need to cooperate to complete tasks. The workflow of these multi-robot tasks involves forming coalitions of robots, assigning them to available tasks, and jointly executing the tasks. In this article, we investigate such a workflow in an application-independent yet realistic setting. We abstract the key properties of tasks and robots and propose three distributed coalition formation and task assignment methods. Distributed methods rely on a timely and accurate exchange of state information in multi-robot systems (MRS). Thus we focus on two important communication aspects: (i) how to achieve consistent coalition formation and task assignment in the presence of communication faults, and (ii) how to reduce the communication effort required for the state updates in the MRS. In particular, we investigate the effect of event-triggered, time-triggered, and hybrid communication. We evaluate our distributed approaches in a simulation study using ns-3 and compare them with centralized methods and different network conditions. We demonstrate the sensitivity of complex missions to failure-prone MRS communication and provide robust, effective, and communication-aware methods for coalition formation and task assignment.