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22条，第1-10条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
A Bio-Inspired Integration Model of Basal Ganglia and Cerebellum for Motion Learning of a Musculoskeletal Robot 期刊论文
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2024, 卷号: 37, 期号: 1, 页码: 82-113
作者:  Zhang, Jinhan;  Chen, Jiahao;  Zhong, Shanlin;  Qiao, Hong
收藏  |  浏览/下载：0/0  |  提交时间：2024/07/03
Basal ganglia and cerebellum  bio-inspired integration model  motion learning  muscu-loskeletal robot  reinforcement learning  
A Bio-Inspired Integration Model of Basal Ganglia and Cerebellum for Motion Learning of a Musculoskeletal Robot 期刊论文
Journal of Systems Science and Complexity, 2024, 卷号: 37, 页码: 82-113
作者:  Jinhan Zhang;  Jiahao Chen;  Shanlin Zhong;  Hong Qiao
Adobe PDF(1513Kb)  |  收藏  |  浏览/下载：43/11  |  提交时间：2024/06/04
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：41/11  |  提交时间：2024/06/04
Musculoskeletal robot  Partial observable  Reinforcement learning  LSTM  Attention  Muscle synergy  
Motion Learning for Musculoskeletal Robots Based on Cortex-Inspired Motor Primitives and Modulation 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2024, 卷号: 16, 期号: 2, 页码: 744-756
作者:  Xiaona Wang;  Jiahao Chen;  Wei Wu
Adobe PDF(3444Kb)  |  收藏  |  浏览/下载：26/6  |  提交时间：2024/06/04
Biologically inspired control  motor preparation  motor primitive  musculoskeletal robot  recurrent neural network (RNN)  
Neural Manifold Modulated Continual Reinforcement Learning for Musculoskeletal Robots 期刊论文
IEEE Transactions on Cognitive and Developmental Systems, 2024, 卷号: 16, 期号: 1, 页码: 86-99
作者:  Chen JH(陈嘉浩);  Chen ZY(陈紫渝);  Yao CJ(姚超竞);  Qiao H(乔红)
Adobe PDF(6732Kb)  |  收藏  |  浏览/下载：49/12  |  提交时间：2024/06/04
Continual reinforcement learning  musculoskeletal robots  neural manifold  recurrent neural network (RNN)  
Robust Motion Learning for Musculoskeletal Robots Based on a Recurrent Neural Network and Muscle Synergies 期刊论文
IEEE Transactions on Automation Science and Engineering, 2024, 页码: 1-16
作者:  Jiahao Chen;  Wu YX(吴亚雄);  Yao CJ(姚超竞);  Huang X(黄销)
Adobe PDF(4084Kb)  |  收藏  |  浏览/下载：39/7  |  提交时间：2024/06/04
Musculoskeletal system  Robots  Muscles  Reinforcement learning  Robustness  Learning systems  Recurrent neural networks  Musculoskeletal robots  recurrent neural network  muscle synergy  robustness  
Memory, attention, and muscle synergies based reinforcement and transfer learning for musculoskeletal robots under imperfect observation 期刊论文
IEEE/ASME Transactions on Mechatronics, 2024, 页码: doi:10.1109/TMECH.2024.3401045
作者:  Chen JH(陈嘉浩);  Wu YX(吴亚雄);  Qiao H(乔红)
Adobe PDF(5646Kb)  |  收藏  |  浏览/下载：17/3  |  提交时间：2024/06/04
Muscle synergy  musculoskeletal robots  reinforcement learning  
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：56/12  |  提交时间：2024/04/23
Brain-inspired intelligent robot  software and hardware  decision making  muscle control  cognitive intelligence  
A Cerebellum-Inspired Prediction and Correction Model for Motion Control of a Musculoskeletal Robot 期刊论文
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2023, 卷号: 15, 期号: 3, 页码: 1209-1223
作者:  Zhang, Jinhan;  Chen, Jiahao;  Wu, Wei;  Qiao, Hong
收藏  |  浏览/下载：133/0  |  提交时间：2023/12/21
Biologically inspired control  cerebellum-inspired model  motion generation  motion learning  musculoskeletal robot  reinforcement learning  
Recent advancements in multimodal human-robot interaction 期刊论文
FRONTIERS IN NEUROROBOTICS, 2023, 卷号: 17, 页码: 21
作者:  Su, Hang;  Qi, Wen;  Chen, Jiahao;  Yang, Chenguang;  Sandoval, Juan;  Laribi, Med Amine
收藏  |  浏览/下载：35/0  |  提交时间：2023/11/17
multi-modal signal processing  multi-modal feedback  multi-modal human-robot interaction  physical human-robot interaction  human-robot interaction