Multi-robot rendezvous in communication-restricted unknown environments via backtracking and semantic frontier-based exploration

The multi-robot rendezvous problem requires coordinating a team of mobile robots to converge at a common location. Efficient decentralized execution with limited communication and in unknown environments can be essential in several applications, but such real-world robotic features are often not captured by theoretical rendezvous frameworks. In this work, we present an approach to this problem that extends traditional frontier-based exploration strategies to facilitate efficient rendezvous in such conditions. Our method allows robots to backtrack their exploration of the environment and exploit semantic knowledge on the map by prioritizing high-connectivity areas like corridors and hallways. We define and evaluate different variants of our method to study a trade-off between the time taken to perform a rendezvous and the amount of discovered area in the environment. Extensive experimental evaluation in ROS using 3D simulations demonstrates the feasibility of our method and its performance improvements over baselines.