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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：256/51  |  提交时间：2023/02/22
Variable impedance skill  Learning from demonstrations  Skills learning  Human-robot interaction  
Development of an Untethered Adaptive Thumb Exoskeleton for Delicate Rehabilitation Assistance 期刊论文
IEEE TRANSACTIONS ON ROBOTICS, 2022, 卷号: 38, 期号: 6, 页码: 3514-3529
作者:  Li, Guotao;  Cheng, Long;  Gao, Ziwen;  Xia, Xiuze;  Jiang, Jingang
收藏  |  浏览/下载：63/0  |  提交时间：2023/03/20
Adaptive mechanism  interaction force  rehabi litation  thumb exoskeleton  
Design and Control of an Underactuated Finger Exoskeleton for Assisting Activities of Daily Living 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 页码: 11
作者:  Li, Houcheng;  Cheng, Long;  Sun, Ning;  Cao, Ran
Adobe PDF(1769Kb)  |  收藏  |  浏览/下载：218/33  |  提交时间：2022/01/27
Exoskeletons  Grasping  Electronics packaging  Kinematics  Senior citizens  Robots  Shape  Admittance control  assistance  finger exoskeleton  preshaping  shape-adaptive grasping  underactuation  
Force Sensorless Admittance Control for Teleoperation of Uncertain Robot Manipulator Using Neural Networks 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 卷号: 51, 期号: 5, 页码: 3282-3292
作者:  Yang, Chenguang;  Peng, Guangzhu;  Cheng, Long;  Na, Jing;  Li, Zhijun
收藏  |  浏览/下载：222/0  |  提交时间：2021/05/31
Robot sensing systems  Force  Robot kinematics  Artificial neural networks  Admittance  Torque  Admittance control  error transformation  force observer  Kinect  neural adaptive control  neural networks (NNs)  robot  
Neural Networks Enhanced Adaptive Admittance Control of Optimized Robot-Environment Interaction 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 卷号: 49, 期号: 7, 页码: 2568-2579
作者:  Yang, Chenguang;  Peng, Guangzhu;  Li, Yanan;  Cui, Rongxin;  Cheng, Long;  Li, Zhijun
收藏  |  浏览/下载：259/0  |  提交时间：2019/07/11
Admittance control  neural networks (NNs)  observer  optimal adaptive control  robot-environment interaction