A Survey of Multifingered Robotic Manipulation: Biological Results, Structural Evolvements, and Learning Methods
文献类型：期刊论文
| 作者 | Li, Yinlin6 ; Wang, Peng4,5,6; Li, Rui3; Tao, Mo1,2; Liu, Zhiyong5,6; Qiao, Hong5,6
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| 刊名 | FRONTIERS IN NEUROROBOTICS
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| 出版日期 | 2022-04-27 |
| 卷号 | 16页码:21 |
| 关键词 | multifingered hand visual-motor control multi-mode fusion hand structural evolution learning-based manipulation |
| ISSN号 | 1662-5218 |
| DOI | 10.3389/fnbot.2022.843267 |
| 通讯作者 | Li, Rui(rui.li@cqu.edu.cn) |
| 英文摘要 | Multifingered robotic hands (usually referred to as dexterous hands) are designed to achieve human-level or human-like manipulations for robots or as prostheses for the disabled. The research dates back 30 years ago, yet, there remain great challenges to effectively design and control them due to their high dimensionality of configuration, frequently switched interaction modes, and various task generalization requirements. This article aims to give a brief overview of multifingered robotic manipulation from three aspects: a) the biological results, b) the structural evolvements, and c) the learning methods, and discuss potential future directions. First, we investigate the structure and principle of hand-centered visual sensing, tactile sensing, and motor control and related behavioral results. Then, we review several typical multifingered dexterous hands from task scenarios, actuation mechanisms, and in-hand sensors points. Third, we report the recent progress of various learning-based multifingered manipulation methods, including but not limited to reinforcement learning, imitation learning, and other sub-class methods. The article concludes with open issues and our thoughts on future directions. |
| WOS关键词 | SYNERGY-BASED CONTROL ; DEXTEROUS MANIPULATION ; PARIETAL CORTEX ; MOTOR ; HAND ; GRASP ; ORIENTATION ; DESIGN ; REPRESENTATION ; OBJECT |
| 资助项目 | National Key Research and Development Plan of China[2020AAA0108902] ; National Natural Science Foundation of China[62003059] ; National Natural Science Foundation of China[61702516] ; China Postdoctoral Science Foundation[2020M673136] ; Open Fund of Science and Technology on Thermal Energy and Power Laboratory, Wuhan 2nd Ship Design and Research Institute, Wuhan, P.R. China[TPL2020C02] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100] ; InnoHK |
| WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:000795888100001 |
| 出版者 | FRONTIERS MEDIA SA |
| 资助机构 | National Key Research and Development Plan of China ; National Natural Science Foundation of China ; China Postdoctoral Science Foundation ; Open Fund of Science and Technology on Thermal Energy and Power Laboratory, Wuhan 2nd Ship Design and Research Institute, Wuhan, P.R. China ; Strategic Priority Research Program of Chinese Academy of Science ; InnoHK |
| 源URL | [http://ir.ia.ac.cn/handle/173211/49437]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 通讯作者 | Li, Rui |
| 作者单位 | 1.Beihang Univ, Sch Automation Sci & Elect Engn, Beijing, Peoples R China 2.Wuhan Second Ship Design & Res Inst, Sci & Technol Thermal Energy & Power Lab, Wuhan, Peoples R China 3.Chongqing Univ, Sch Automation, Chongqing, Peoples R China 4.Chinese Acad Sci, Hong Kong Inst Sci & Innovat, Ctr Artificial Intelligence & Robot, Hong Kong, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Automation, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Yinlin,Wang, Peng,Li, Rui,et al. A Survey of Multifingered Robotic Manipulation: Biological Results, Structural Evolvements, and Learning Methods[J]. FRONTIERS IN NEUROROBOTICS,2022,16:21. |
| APA | Li, Yinlin,Wang, Peng,Li, Rui,Tao, Mo,Liu, Zhiyong,&Qiao, Hong.(2022).A Survey of Multifingered Robotic Manipulation: Biological Results, Structural Evolvements, and Learning Methods.FRONTIERS IN NEUROROBOTICS,16,21. |
| MLA | Li, Yinlin,et al."A Survey of Multifingered Robotic Manipulation: Biological Results, Structural Evolvements, and Learning Methods".FRONTIERS IN NEUROROBOTICS 16(2022):21. |
入库方式： OAI收割
来源：自动化研究所
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