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Video s3
    Details
    Presenter(s)
    Jung-Chun Liu Headshot
    Display Name
    Jung-Chun Liu
    Affiliation
    Affiliation
    National Taiwan University
    Country
    Author(s)
    Display Name
    Jung-Chun Liu
    Affiliation
    Affiliation
    National Taiwan University
    Display Name
    Tsung-Te Liu
    Affiliation
    Abstract

    A multi-robot system has advantages in complex tasks, where formation control is one of the most critical and fundamental tasks. For small-sized, autonomous, and enduring robots, realizing high energy and area efficiency is extremely important. This paper presents a novel approach that combines swarm intelligence and reinforcement learning to realize accurate and reliable operations. An area-energy-efficient hardware architecture is proposed to perform formation control in a distributed robotic system. The proposed system demonstrates substantially lower cost and power consumption when compared with the state-of-the-art designs.

    Slides
    • Multi-Robot Formation Control Using Collective Behavior Model and Reinforcement Learning (application/pdf)