Biblio

Decentralized planning for multi-agent systems,such as fleets of robots in a search-and-rescue operation, is oftenconstrained by limitations on how agents can communicate witheach other. One such limitation is the case when agents cancommunicate with each other only when they are in line-of-sight (LOS). Developing decentralized planning methods thatguarantee safety is difficult in this case, as agents that areoccluded from each other might not be able to communicateuntil it’s too late to avoid a safety violation. In this paper, wedevelop a decentralized planning method that explicitly avoidssituations where lack of visibility of other agents would leadto an unsafe situation. Building on top of an existing Rapidly-exploring Random Tree (RRT)-based approach, our methodguarantees safety at each iteration. Simulation studies showthe effectiveness of our method and compare the degradationin performance with respect to a clairvoyant decentralizedplanning algorithm where agents can communicate despite notbeing in LOS of each other.

We study the control of monotone systems when the objective is to maintain trajectories in a directed set (that is, either upper or lower set) within a signal space. We define the notion of a directed alternating simulation relation and show how it can be used to tackle common bottlenecks in abstraction-based controller synthesis. First, we develop sparse abstractions to speed up the controller synthesis procedure by reducing the number of transitions. Next, we enable a compositional synthesis approach by employing directed assume-guarantee contracts between systems. In a vehicle traffic network example, we synthesize an intersection signal controller while dramatically reducing runtime and memory requirements compared to previous approaches.