中文版 | English

在结果中检索

CASIA OpenIR
（本次检索基于用户作品认领结果）

浏览/检索结果: 共13条，第1-10条 帮助

限定条件        
已选(0)清除 条数/页：   排序方式：
Compliant peg-in-hole assembly for nonconvex axisymmetric components based on attractive region in environment 期刊论文
Robotica, 2023, 卷号: 41, 期号: 8, 页码: 2314 - 2336
作者:  Liu Y(刘洋);  Chen ZY(陈紫渝);  Qiao H(乔红);  Gan S(甘帅)
Adobe PDF(2042Kb)  |  收藏  |  浏览/下载：51/18  |  提交时间：2024/06/05
automation  motion planning  nonconvex axisymmetric parts  high-precision peg-in-hole assembly  constraint region analysis  attractive region in environment  
A memory and attention-based reinforcement learning for musculoskeletal robots with prior knowledge of muscle synergies 期刊论文
Robotic Intelligence and Automation, 2024, 卷号: 44, 期号: 2, 页码: 316-333
作者:  Xiaona Wang;  Jiahao Chen;  Hong Qiao
Adobe PDF(2591Kb)  |  收藏  |  浏览/下载：53/15  |  提交时间：2024/06/04
Musculoskeletal robot  Partial observable  Reinforcement learning  LSTM  Attention  Muscle synergy  
Brain-inspired Intelligent Robotics: Theoretical Analysis and Systematic Application 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 1, 页码: 1-18
作者:  Hong Qiao;  Ya-Xiong Wu;  Shan-Lin Zhong;  Pei-Jie Yin;  Jia-Hao Chen
Adobe PDF(2207Kb)  |  收藏  |  浏览/下载：71/16  |  提交时间：2024/04/23
Brain-inspired intelligent robot  software and hardware  decision making  muscle control  cognitive intelligence  
Robotic Inserting a Moving Object using Visual-based Control with Time-Delay Compensator 期刊论文
IEEE Transactions on Industrial Informatics, 2023, 页码: 1 - 11
作者:  Jianhua Su;  Lili Wang;  Chuankai Liu;  Hong Qiao
Adobe PDF(1359Kb)  |  收藏  |  浏览/下载：216/80  |  提交时间：2023/06/27
Trajectory-based Split Hindsight Reverse Curriculum Learning 会议论文
, Prague, Czech Republic, 2021-9
作者:  Wu, Jiaxi;  Zhang, Dianmin;  Zhong, Shanlin;  Qiao, Hong
Adobe PDF(5094Kb)  |  收藏  |  浏览/下载：242/60  |  提交时间：2022/06/14
Reinforcement Learning  Curriculum Learning  
Tracking of Uncertain Robotic Manipulators Using Event-Triggered Model Predictive Control With Learning Terminal Cost 期刊论文
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2022, 卷号: 19, 期号: 4, 页码: 2801-2815
作者:  Kang, Erlong;  Qiao, Hong;  Chen, Ziyu;  Gao, Jie
Adobe PDF(4203Kb)  |  收藏  |  浏览/下载：463/160  |  提交时间：2022/06/06
Model predictive control  robotic manipulator  leaning terminal cost  neural networks  event-triggered mechanism  unknown dynamics  
A survey of brain-inspired intelligent robots with integration of vision, decision, motion control and musculoskeletal systems 期刊论文
IEEE Transactions on Cybernetics, 2021, 卷号: 暂无, 期号: 暂无, 页码: 暂无
作者:  Hong Qiao;  Jiahao Chen;  Xiao Huang
Adobe PDF(1001Kb)  |  收藏  |  浏览/下载：245/59  |  提交时间：2021/06/01
Brain-inspired intelligent robots  musculoskeletal robots  visual cognition  decision making  muscle control  
Adaptive-Neural-Network-Based Trajectory Tracking Control for a Nonholonomic Wheeled Mobile Robot With Velocity Constraints 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 卷号: 68, 期号: 6, 页码: 5057-5067
作者:  Chen, Ziyu;  Liu, Yang;  He, Wei;  Qiao, Hong;  Ji, Haibo
Adobe PDF(1673Kb)  |  收藏  |  浏览/下载：338/17  |  提交时间：2021/04/06
Mobile robots  Lyapunov methods  Adaptive systems  Artificial neural networks  Automation  Adaptive neural networks  barrier Lyapunov function (BLF)  velocity constraint  wheeled mobile robot (WMR)  
Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints 期刊论文
ISA TRANSACTIONS, 2021, 卷号: 109, 页码: 89-101
作者:  Kang, Erlong;  Qiao, Hong;  Gao, Jie;  Yang, Wenjing
Adobe PDF(942Kb)  |  收藏  |  浏览/下载：401/81  |  提交时间：2021/03/29
Model predictive control  Neural network  Robotic manipulator  Unknown dynamics  Online learning estimation  Input constraints  
Connecting Model-Based and Model-Free Control With Emotion Modulation in Learning Systems 期刊论文
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, 卷号: 10, 期号: 4, 页码: 1-15
作者:  Huang, Xiao;  Wu, Wei;  Qiao, Hong
浏览  |  Adobe PDF(1614Kb)  |  收藏  |  浏览/下载：300/100  |  提交时间：2020/06/09
Brain-inspired computing  decision-making  emotion modulation  emotion-cognition interactions  reinforcement learning