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While significant advances have been made for single-agent perception, manyapplications require multiple sensing agents and cross-agent communication dueto benefits such as coverage and robustness. It is therefore critical todevelop frameworks which support multi-agent collaborative perception in adistributed and bandwidth-efficient manner. In this paper, we address thecollaborative perception problem, where one agent is required to perform aperception task and can communicate and share information with other agents onthe same task. Specifically, we propose a communication framework by learningboth to construct communication groups and decide when to communicate. Wedemonstrate the generalizability of our framework on two different perceptiontasks and show that it significantly reduces communication bandwidth whilemaintaining superior performance.

When2com: Multi-Agent Perception via Communication Graph Grouping