Communication-constrained Path Planning for Multi-Rover Exploration on the Lunar Surface

The recent rise in the interest for lunar exploration have led to the development of several robotic missions with the aim of mapping resources and conducting prospecting activities. These missions will greatly benefit from the use of robotic teams to efficiently explore large areas within a limited time frame while achieving mission objectives in a coordinated manner. This paper addresses the challenge of optimizing coordination for collaborative multi-robot systems. We propose a communication-constrained path planning approach utilizing a previously developed deterministic radio propagation model and theory of graph connectivity. The cost function for the planner implements a graph-based path finding coupled with a heuristic method to find the shortest path while maintaining communication links with the nearest agents. Several simulations were carried out to evaluate the performance of the planner by varying the weights of the constraints. The results demonstrate that a multi-hop communication between the agents with a reliable relay network enables sharing of information, thus reducing the revisitation time and enabling safe exploration on the lunar surface.