Distributed Control of Robotic Swarms from Reactive High-Level Specifications

This paper presents a distributed strategy for automatically synthesizing controls for robotic swarms such that they achieve reactive, high-level formation tasks. In our framework, a user specifies formation and location-based swarm tasks, which may include reactions to environmental events, using linear temporal logic. Then, we synthesize a centralized finite automaton that represents the symbolic behavior of the swarm. To execute the automaton, we develop an auction-based decentralized algorithm that assigns robots to different locations and formations using only information from neighboring robots. To guarantee that the swarm can achieve the specified high-level tasks, we use integer programming to obtain the maximum and minimum number of robots that need to be sent to different locations during each symbolic transition, and we incorporate the constraints on sub-swarm sizes into the auction-based assignment algorithm. We demonstrate our control framework in simulation and with ten Anki-Vector robots in the lab.