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Automatic Robotic Cranium-Milling: A Motion Control Study of In Vitro Animal Experiments 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 页码: 1-14
作者:  Bian GB(边桂彬);  Qian C(钱琛);  Li Z(李桢);  Ye Q(叶强);  Ge PC(葛培聪);  Zhao JZ(赵继宗)
Adobe PDF(2827Kb)  |  收藏  |  浏览/下载：57/14  |  提交时间：2024/05/28
Autonomous craniotomy robot  model-free adaptive nonlinear force control  skull-milling breakthrough detection  in vitro animal experiments  
CASOG: Conservative Actor–Critic With SmOoth Gradient for Skill Learning in Robot-Assisted Intervention 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2023, 页码: 10
作者:  Li, Hao;  Zhou, Xiao-Hu;  Xie, Xiao-Liang;  Liu, Shi-Qi;  Feng, Zhen-Qiu;  Hou, Zeng-Guang
收藏  |  浏览/下载：94/0  |  提交时间：2024/02/22
Deep neural network  offline reinforcement learning  robot-assisted intervention  vascular robotic system  
Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 2, 页码: 301-328
作者:  Yuchuang Tong;  Haotian Liu;  Zhengtao Zhang
Adobe PDF(7587Kb)  |  收藏  |  浏览/下载：172/51  |  提交时间：2024/01/23
Future trends and challenges  humanoid robots  human-robot interaction  key technologies  potential applications  
Learning Human-to-Robot Dexterous Handovers for Anthropomorphic Hand 期刊论文
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2023, 卷号: 15, 期号: 3, 页码: 1224-1238
作者:  Duan, Haonan;  Wang, Peng;  Li, Yiming;  Li, Daheng;  Wei, Wei
Adobe PDF(10850Kb)  |  收藏  |  浏览/下载：147/19  |  提交时间：2023/12/21
Anthropomorphic hand  handovers  human-robot interaction  
Soft Magnetic Skin's Deformation Analysis for Tactile Perception 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2023, 卷号: 70, 期号: 12, 页码: 12883-12893
作者:  Gui, Mei-Jiang;  Zhou, Xiao-Hu;  Xie, Xiao-Liang;  Liu, Shi-Qi;  Feng, Zhen-Qiu;  Hou, Zeng-Guang
Adobe PDF(2789Kb)  |  收藏  |  浏览/下载：164/9  |  提交时间：2023/11/17
Soft magnetic skins  deformations analy-sis  dynamic Young's modulus (DYM)  finite-element simulation  tactile perception  
Hierarchical Policy Learning With Demonstration Learning for Robotic Multiple Peg-in-Hole Assembly Tasks 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 卷号: 19, 期号: 10, 页码: 10254-10264
作者:  Yan, Shaohua;  Xu, De;  Tao, Xian
Adobe PDF(4845Kb)  |  收藏  |  浏览/下载：134/13  |  提交时间：2023/11/17
Assembly model  demonstration learning (DL)  force-based control algorithm  hierarchical reinforcement learning (HRL)  peg-in-hole assembly  
A Survey on Reinforcement Learning Methods in Bionic Underwater Robots 期刊论文
BIOMIMETICS, 2023, 卷号: 8, 期号: 2, 页码: 29
作者:  Tong, Ru;  Feng, Yukai;  Wang, Jian;  Wu, Zhengxing;  Tan, Min;  Yu, Junzhi
Adobe PDF(1260Kb)  |  收藏  |  浏览/下载：149/19  |  提交时间：2023/11/17
bionic underwater robot  reinforcement learning  robotic fish  intelligent control  
Robotic Automatic Drilling for Craniotomy: Algorithms and In Vitro Animal Experiments 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2023, 页码: 12
作者:  Bian, Gui-Bin;  Wei, Bing-Ting;  Li, Zhen;  Ge, Peicong;  Chen, Zhang;  Qian, Chen;  Wang, Jie;  Fu, Pan;  Zhao, Jizong
Adobe PDF(2827Kb)  |  收藏  |  浏览/下载：138/11  |  提交时间：2023/11/17
Drilling  Robots  Force  Robot sensing systems  Skull  Feeds  Service robots  Autonomous drilling  craniotomy robot  feed velocity and force constraint control  in vitro experiment  skull-dura boundary detection  
A neural network based framework for variable impedance skills learning from demonstrations 期刊论文
ROBOTICS AND AUTONOMOUS SYSTEMS, 2023, 卷号: 160, 页码: 10
作者:  Zhang, Yu;  Cheng, Long;  Cao, Ran;  Li, Houcheng;  Yang, Chenguang
Adobe PDF(3824Kb)  |  收藏  |  浏览/下载：410/71  |  提交时间：2023/02/22
Variable impedance skill  Learning from demonstrations  Skills learning  Human-robot interaction  
Discrete soft actor-critic with auto-encoder on vascular robotic system 期刊论文
ROBOTICA, 2022, 页码: 12
作者:  Li, Hao;  Zhou, Xiao-Hu;  Xie, Xiao-Liang;  Liu, Shi-Qi;  Gui, Mei-Jiang;  Xiang, Tian-Yu;  Wang, Jin-Li;  Hou, Zeng-Guang
Adobe PDF(715Kb)  |  收藏  |  浏览/下载：277/7  |  提交时间：2023/01/09
surgical robots  vascular robotic system  automation  reinforcement learning  deep neural network