Search and rescue with sparsely connected swarms

Designing and deploying autonomous swarms capable of performing collective tasks in real-world is extremely challenging. One drawback of getting out of the lab is that realistic tasks involve long distances with limited numbers of robots, leading to sparse and intermittent connectivity. As an example, search and rescue requires robots to coordinate in their search, and relay the information of found targets. The search’s effectiveness is greatly reduced if robots must stay close to maintain connectivity. This paper proposes a decentralized search system that only requires sporadic connectivity and allows information diffusion through the swarm whenever possible. Our robots share and update a distributed belief map, to coordinate the search. Once a target is detected, the robots form a communication relay between a base station and the target’s position. We show the applicability of our system both in simulation and with real-world experiments with a small swarm of drones.