Selective Comms

Reducing communication by self-triggered control and forming subteams

Many challenges exist in the long-term autonomy of multi-robot systems, such as limited onboard battery capacity, heavy computation and communication load, and dangerous and uncertain outer environments. Among these challenges, our research focuses on reducing communication costs during coordination. Particularly, leveraging self-triggered control, we designed a “when to communicate” strategy that decides when a robot in the team should communicate to seek up-to-date information and when it is safe to operate with possibly outdated information. Even though the communication is restricted, this self-triggered strategy achieves similar performance to the all-time communication strategy, in theory, simulations, and a proof-of-concept experiment. To further reduce communication costs, we devised a “who to communicate with” strategy by forming robot subteams. We proposed a polynomial-time assignment algorithm that provides a provably near-optimal performance even though the robots can only communicate within subteams.

ICRA’17, T-ASE’18: Active target tracking with self-triggered communications in multi-robot teams (left video).
ICRA’20+T-RO’19: Sensor assignment algorithms to improve observability while tracking targets (right video).