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A modified cartesian space DMPs model for robot motion generation
Liu NL(刘乃龙)1,2,3; Liu ZM(刘钊铭)1,2,3; Cui L(崔龙)1,2
Department机器人学研究室
Conference Name12th International Conference on Intelligent Robotics and Applications, ICIRA 2019
Conference DateAugust 8-11, 2019
Conference PlaceShenyang, China
Source PublicationIntelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings
PublisherSpringer Verlag
Publication PlaceBerlin
2019
Pages76-85
Indexed ByEI
EI Accession number20193407325820
Contribution Rank1
ISSN0302-9743
ISBN978-3-030-27528-0
KeywordDynamic movement primitives DMPs Robot learning Learning from demonstration
AbstractDMPs (dynamic movement primitives) are a method to generate trajectory planning or control signal for complex robot movements. Each DMP is a nonlinear dynamical system which can be used as a primitive action for complex movements. The origin DMPs are used to model the robot joint space motion, however in many cases, robot motions are defined in Cartesian space, the model of Cartesian space is necessary. A Cartesian space DMPs variant is proposed which adds a dynamical quaternions goal subsystem to make the generated cartesian space twist more smooth and steady in the initial stage in this paper. This DMPs variant can be useful in some robot tasks which often require low speed operations, such as contact operation. © Springer Nature Switzerland AG 2019.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/25503
Collection机器人学研究室
Corresponding AuthorLiu NL(刘乃龙)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences (CAS), Shenyang 110016, China
3.University of Chinese Academy of Sciences (CAS), Beijing 100049, China
Recommended Citation
GB/T 7714
Liu NL,Liu ZM,Cui L. A modified cartesian space DMPs model for robot motion generation[C]. Berlin:Springer Verlag,2019:76-85.
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