Matrix-Based Information Sharing Approach for Dynamic Robot Teams

Abstract

In wireless connected robot swarms, information sharing is necessary for robots to cooperatively achieve joint goals under a partially observable environment. Despite significant progress on this problem, existing researchers have not adequately dealt with the case that robots broadcast messages to multiple members with a dynamically changing communication medium. In this paper, we propose an effective information sharing approach for dynamic robot teams. By using a matrix representation for information distribution, the network structure and information needs, this model allows quick reasoning through a single computation. Following our theoretical analysis, this approach can perform as the MDP model for small teams when states are fully observable. In addition, we designed heuristic algorithms to help robots adapt to dynamic network connections and information distribution in large teams. Empirical simulation results manifest that the approach performs well in uncertain environments to effectively balance sharing information with minimizing communication costs.

Keywords

• Information sharing
• dynamic robot teams
• matrix-based computing
• Markov decision process