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基于强化学习的多指机器人手灵巧操作综述

Dexterous Manipulation for Multi-Fingered Robotic Hands With Reinforcement Learning: A Review.

作者信息

Yu Chunmiao, Wang Peng

机构信息

Institute of Automation, Chinese Academy of Sciences, Beijing, China.

School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.

出版信息

Front Neurorobot. 2022 Apr 25;16:861825. doi: 10.3389/fnbot.2022.861825. eCollection 2022.

Abstract

With the increasing demand for the dexterity of robotic operation, dexterous manipulation of multi-fingered robotic hands with reinforcement learning is an interesting subject in the field of robotics research. Our purpose is to present a comprehensive review of the techniques for dexterous manipulation with multi-fingered robotic hands, such as the model-based approach without learning in early years, and the latest research and methodologies focused on the method based on reinforcement learning and its variations. This work attempts to summarize the evolution and the state of the art in this field and provide a summary of the current challenges and future directions in a way that allows future researchers to understand this field.

摘要

随着对机器人操作灵活性需求的不断增加,利用强化学习对多指机器人手进行灵巧操作是机器人研究领域一个有趣的课题。我们的目的是对多指机器人手灵巧操作的技术进行全面综述,例如早年基于模型的无学习方法,以及专注于基于强化学习及其变体方法的最新研究和方法。这项工作试图总结该领域的发展历程和现状,并以一种让未来研究人员能够理解该领域的方式,对当前的挑战和未来方向进行总结。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b61/9083362/5b33726de6b6/fnbot-16-861825-g0003.jpg

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