Knowledge Commons of Institute of Automation,CAS
A robotic shared control teleoperation method based on learning from demonstrations | |
Xi, Bao1,2; Wang, Shuo1,2,3; Ye, Xuemei1; Cai, Yinghao1; Lu, Tao1; Wang, Rui1 | |
发表期刊 | INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS |
ISSN | 1729-8814 |
2019-07-12 | |
卷号 | 16期号:4页码:1-13 |
摘要 | In teleoperation, the operator is often required to command the motion of the remote robot and monitor its behavior. However, such an interaction demands a heavy workload from a human operator when facing with complex tasks and dynamic environments. In this article, we propose a shared control method to assist the operator in the manipulation tasks to reduce the workload and improve the efficiency. We adopt a task-parameterized hidden semi-Markov model to learn a manipulation skill from several human demonstrations. We utilize the learned model to predict the manipulation target given the current observed robotic motion trajectory and subsequently estimate the desired robotic motion given the current input of the operator. The estimated robotic motion is then utilized to correct the input of the operator to provide manipulation assistance. In addition, a set of virtual reality devices are used to capture the operator's motion and display the vision feedback from the remote site. We evaluate our approach through two manipulation tasks with a dual-arm robot. The experimental results show the effectiveness of the proposed method. |
关键词 | Dual arm hidden semi-Markov model goal prediction operation assistance virtual reality |
DOI | 10.1177/1729881419857428 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Science and Technology on Space Intelligent Control Laboratory for National Defense[KGJZDSYS-2018-09] ; National Natural Science Foundation of China[61773378] ; National Natural Science Foundation of China[U1713222] ; National Natural Science Foundation of China[61703401] ; Early Career Development Award of SKLMCCS ; National Key R&D Program of China[2017YFB1300202] ; National Key R&D Program of China[2017YFB1300202] ; Early Career Development Award of SKLMCCS ; National Natural Science Foundation of China[61703401] ; National Natural Science Foundation of China[U1713222] ; National Natural Science Foundation of China[61773378] ; Science and Technology on Space Intelligent Control Laboratory for National Defense[KGJZDSYS-2018-09] |
WOS研究方向 | Robotics |
WOS类目 | Robotics |
WOS记录号 | WOS:000475766600001 |
出版者 | SAGE PUBLICATIONS INC |
七大方向——子方向分类 | 智能机器人 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/27745 |
专题 | 多模态人工智能系统全国重点实验室_智能机器人系统研究 |
通讯作者 | Xi, Bao |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Techn, Shanghai, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xi, Bao,Wang, Shuo,Ye, Xuemei,et al. A robotic shared control teleoperation method based on learning from demonstrations[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2019,16(4):1-13. |
APA | Xi, Bao,Wang, Shuo,Ye, Xuemei,Cai, Yinghao,Lu, Tao,&Wang, Rui.(2019).A robotic shared control teleoperation method based on learning from demonstrations.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,16(4),1-13. |
MLA | Xi, Bao,et al."A robotic shared control teleoperation method based on learning from demonstrations".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 16.4(2019):1-13. |
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