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arXiv · 2105.06118

An Upper Confidence Bound for Simultaneous Exploration and Exploitation in Heterogeneous Multi-Robot Systems

Ki Myung Brian Lee·Felix H. Kong·Ricardo Cannizzaro·Jennifer L. Palmer·David Johnson·Chanyeol Yoo·Robert Fitch
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Abstract

Heterogeneous multi-robot systems are advantageous for operations in unknown environments because functionally specialised robots can gather environmental information, while others perform tasks. We define this decomposition as the scout-task robot architecture and show how it avoids the need to explicitly balance exploration and exploitation~by permitting the system to do both simultaneously. The challenge is to guide exploration in a way that improves overall performance for time-limited tasks. We derive a novel upper confidence bound for simultaneous exploration and exploitation based on mutual information and present a general solution for scout-task coordination using decentralised Monte Carlo tree search. We evaluate the performance of our algorithms in a multi-drone surveillance scenario in which scout robots are equipped with low-resolution, long-range sensors and task robots capture detailed information using short-range sensors. The results address a new class of coordination problem for heterogeneous teams that has many practical applications.

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Ki Myung Brian Lee, Felix H. Kong, Ricardo Cannizzaro, Jennifer L. Palmer, David Johnson, Chanyeol Yoo, Robert Fitch. 2021-05-13. An Upper Confidence Bound for Simultaneous Exploration and Exploitation in Heterogeneous Multi-Robot Systems. https://arxiv.org/abs/2105.06118

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