This paper develops a controller synthesis approach for a multi-agent system (MAS) with intermittent communication. We adopt a leader-follower scheme, where a mobile leader with absolute position sensors switches among a set of followers without absolute position sensors to provide each follower with intermittent state information. We model the MAS as a switched system. The followers are to asymptotically reach a predetermined consensus state. To guarantee the stability of the switched system and the consensus of the followers, we derive maximum and minimal dwell-time conditions to constrain the intervals between consecutive time instants at which the leader should provide state information to the same follower. Furthermore, the leader needs to satisfy practical constraints such as charging its battery and staying in specific regions of interest. Both the maximum and minimum dwell-time conditions and these practical constraints can be expressed by metric temporal logic (MTL) specifications. We iteratively compute the optimal control inputs such that the leader satisfies the MTL specifications, while guaranteeing stability and consensus of the followers. We implement the proposed method on a case study with three mobile robots as the followers and one quadrotor as the leader.
I. INTRODUCTIONCoordination strategies for multi-agent systems (MAS) have been traditionally designed under the assumption that state feedback is continuously available. However, continuous communication over a network is often impractical, especially in mobile robot applications where shadowing and fading in the wireless communication can cause unreliability, and each agent has limited energy resources [1], [2].Due to these constraints, there is a strong interest in developing MAS coordination methods that rely on intermittent information over a communication network. The results in [3]-[8] develop event-triggered and self-triggered controllers that utilize sampled data from networked agents only when triggered by conditions that ensure desired stability and performance properties. However, these results require a network represented by a strongly connected graph to enable agent coordination. This requirement of a strongly connected network induces constraints on the motion of the individual agents and additional maneuvers that may deviate from their primary purpose. Event-triggered and self-triggered control