中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共5条，第1-5条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
ACDER: Augmented Curiosity-Driven Experience Replay 会议论文
, Paris, France, 2020.05.31-2020.08.31
作者:  Li, Boyao;  Lu, Tao;  Li, Jiayi;  Lu, Ning;  Cai, Yinghao;  Wang, Shuo
Adobe PDF(3303Kb)  |  收藏  |  浏览/下载：239/75  |  提交时间：2020/08/27
Real-Sim-Real Transfer for Real-World Robot Control Policy Learning with Deep Reinforcement Learning 期刊论文
APPLIED SCIENCES-BASEL, 2020, 卷号: 10, 期号: 5, 页码: 16
作者:  Liu, Naijun;  Cai, Yinghao;  Lu, Tao;  Wang, Rui;  Wang, Shuo
Adobe PDF(6287Kb)  |  收藏  |  浏览/下载：241/59  |  提交时间：2020/06/02
robot  policy learning  reality gap  simulated environment  deep reinforcement learning  
Periodic impulse signal separation based on resonance-based sparse signal decomposition and its application to the fault detection of rolling bearing 期刊论文
MEASUREMENT & CONTROL, 2020, 卷号: 53, 期号: 3-4, 页码: 601-612
作者:  Juan, Du;  Yan, Lu;  Xian, Tao;  Yu, Zheng;  Chu, Chen Guo
收藏  |  浏览/下载：176/0  |  提交时间：2020/07/06
Resonance-based sparse signal decomposition  Q-factor  empirical mode decomposition  energy operator demodulating  fault detection  
Manipulation Skill Learning on Multi-step Complex Task Based on Explicit and Implicit Curriculum Learning 期刊论文
SCIENCE CHINA Information Sciences, 2020, 卷号: 0, 期号: 0, 页码: 0-0
作者:  Liu, Naijun;  Lu, Tao;  Cai, Yinghao;  Wang, Rui;  Wang, Shuo
Adobe PDF(2456Kb)  |  收藏  |  浏览/下载：156/66  |  提交时间：2020/09/27
robot  manipulation skill learning  multi-step complex task  curriculum learning  
Real-world Robot Reaching Skill Learning Based on Deep Reinforcement Learning 会议论文
, Hefei, China, 2020
作者:  Liu, Naijun;  Lu, Tao;  Cai, Yinghao;  Wang, Rui;  Wang, Shuo
Adobe PDF(436Kb)  |  收藏  |  浏览/下载：142/46  |  提交时间：2020/09/27