Distributed Dynamic Matching of Two Groups of Agents with Different Sensing Ranges
Yuto Watanabe, Kazunori Sakurama · 2022 IEEE 61st Conference on Decision and Control (CDC) · 2022
This paper provides a new distributed controller for dynamic matching of multiple agents with different sensing ranges. Dynamic matching is a problem of making pairs from two agent groups to make the states of paired agents converge to the same value. In this problem, agents autonomously find their partners only with local information and can flexibly adapt to the change of environments. First, we develop a distributed controller design methodology for multi-agent systems over a class of directed graphs, which is applicable to various tasks. We show the convergence of the states and the performance enhancement from previous methods. Next, via the developed method, we design a distributed controller for dynamic matching and derive sufficient conditions for successful matching. Finally, we demonstrate the effectiveness of our proposed method through numerical examples.