Communication-Aware Multi-robot Coordination with Submodular Maximization
This addresses communication maintenance in multi-robot systems for tasks like information gathering, but it is incremental as it builds on existing submodular maximization methods.
The paper tackles the problem of multi-robot coordination where maximizing submodular objectives can disrupt communication networks, proposing a communication-aware submodular maximization (CSM) problem and a two-stage heuristic algorithm. The algorithm shows only a slight average performance decrease compared to pure greedy strategies in simulations.
Submodular maximization has been widely used in many multi-robot task planning problems including information gathering, exploration, and target tracking. However, the interplay between submodular maximization and communication is rarely explored in the multi-robot setting. In many cases, maximizing the submodular objective may drive the robots in a way so as to disconnect the communication network. Driven by such observations, in this paper, we consider the problem of maximizing submodular function with connectivity constraints. Specifically, we propose a problem called Communication-aware Submodular Maximization (CSM), in which communication maintenance and submodular maximization are jointly considered in the decision-making process. One heuristic algorithm that consists of two stages, i.e. \textit{topology generation} and \textit{deviation minimization} is proposed. We validate the formulation and algorithm through numerical simulation. We find that our algorithm on average suffers only slightly performance decrease compared to the pure greedy strategy.