SMC-Searcher: Signal Mediated Coordination for Decentralized Multi-Robot Adversarial Moving Target Search

This paper investigates the multi-robot adversarial search (MuRAS) problem, which requires coordinating a team of mobile robots to search for one adversarially moving target in discrete environments. One unique challenge that MuRAS poses to the multi-robot search community in comparison to the canonical multi-robot efficient search (MuRES) problem is that the target adapts its motion model to avoid being detected by the robot team, rendering the environment non-stationary and degrading the performance of most MuRES solutions. In this paper, we first formulate MuRAS as a minimax optimization problem, i.e., the zero sum game, and then propose an algorithm, namely SMC-Searcher, a signal mediated coordination method for decentralized adversarial moving target search. SMC-Searcher enhances the canonical multi-robot search strategy by injecting a global coordination signal that prompts different and thus diversified search strategies for each robot. We demonstrate that SMC-Searcher achieves the best performance, in terms of the target's expected capture time when compared to existing multi-robot search strategies, with a simple yet illustrative example, and further compare its performance with state-of-the-art multi-robot search strategies in two canonical multi-robot search environments, namely OFFICE and MUSEUM. Additionally, SMC-Searcher is integrated into a real multi-robot system for moving target search in a self-constructed indoor environment.