Empower dexterous robotic hand for human-centric smart manufacturing: A perception and skill learning perspective

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Benhua Gao , Junming Fan , Pai Zheng
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引用次数: 0

Abstract

Recent rapid developments of dexterous robotic hands have greatly enhanced the manipulative capabilities of robots, enabling them to perform industrial tasks in human-like dexterity. These advancements not only enhance operational efficiency but also liberate human operators from monotonous tasks, allowing them to focus on creative and intellectually demanding. Despite the considerable attention robotic hands have garnered, existing reviews tend to focus on isolated topics, failing to provide a comprehensive perspective of the manufacturing sector. To empower robotic hands in human-centric smart manufacturing, this paper explores the latest research on holistic perception and dexterous skill learning of robotic hands. Specifically, the perceptual challenges in dexterous manipulation concerning different entities are investigated, including human hand perception, object inside-hand and outside-hand perception based on vision or tactility, and hand-object interactions, which help robots accurately understand environmental information. Furthermore, learning-based control methods are discussed, enhancing the execution capabilities of robotic hands through learning from scratch and learning from human demonstrations. Lastly, this paper identifies current challenges and offers several promising directions for future developments.
为以人为中心的智能制造赋予灵巧的机器人手:感知和技能学习的视角
近年来,灵巧机械手的快速发展极大地提高了机器人的操作能力,使其能够像人一样灵巧地完成工业任务。这些进步不仅提高了操作效率,而且将人类操作员从单调的任务中解放出来,使他们能够专注于创造性和智力要求。尽管机器人手已经获得了相当多的关注,但现有的评论往往集中在孤立的主题上,未能提供制造业的全面视角。为了使机器人手能够实现以人为中心的智能制造,本文探讨了机器人手整体感知和灵巧技能学习的最新研究进展。具体而言,研究了不同实体灵巧操作中的感知挑战,包括人的手感知、基于视觉或触觉的物体内手和手外感知,以及帮助机器人准确理解环境信息的手-物交互。此外,还讨论了基于学习的控制方法,通过从零开始学习和从人类演示中学习来提高机器人手的执行能力。最后,本文指出了当前的挑战,并为未来的发展提供了几个有希望的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
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