Résumé (EN)

Operations in unpredictable environments require coordinating teams of robots. This coordination implies peer-to-peer communication between the team's robots, resource allocation, and coordination. We address the problem of autonomous robots which alternate between execution of individual tasks and peer-to-peer communication. Each robot keeps in its permanent memory a set of locations where it can meet some of the other robots. The proposed protocol is constructed by two layered modules (sub-algorithms: a self-stabilizing scheduling and a construction of a minimum-hop path forest). The first self-stabilizing algorithm solves the management of visits to these locations ensuring that, after the stabilizing phase, every visit to a location will lead to a communication. We model the untimed behaviour of a robot by a Petri net and the timed behaviour by an (infinite) Discrete Time Markov Chain. Theoretical results in this area are then combined in order to establish the proof of the algorithm. The second self-stabilizing algorithm computes the minimum-hop path between a specific robot's location and the locations of all the other robots of the system in order to implement routing.