Presentation 2020-10-21
[招待講演]NNによってモデル化された運動学・動力学に基づくロボット制御
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) As complexity of robots and environments increases, analytically formulating their kinematics and dynamics becomes difficult. Neural networks have been widely used as a way of functional approximation for this case from the early days of robotics, and with the rise of deep learning in recent years, the scope of use has been greatly expanded. On the other hand, understanding their results in terms of well-established robot control theory based on analytical kinematic and dynamic models of robots is increasingly difficult due to the weak relationship between them. In this talk, several methods where robot's kinematics and dynamics are modeled by neural networks but the understanding and the control are carried out in terms of well-established theories based on analytical models.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Neural Networks / Model Predictive Control / Musculoskeletal Robot
Paper # IBISML2020-20
Date of Issue 2020-10-13 (IBISML)

Conference Information
Committee IBISML
Conference Date 2020/10/20(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Organized Sessions on Frontiers of Machine Learning and General Sessions
Chair Ichiro Takeuchi(Nagoya Inst. of Tech.)
Vice Chair Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo)
Secretary Masashi Sugiyama(AIST) / Koji Tsuda(NTT)
Assistant Atsuyoshi Nakamura(Hokkaido Univ.) / Shigeyuki Oba(Kyoto Univ.)

Paper Information
Registration To Technical Committee on Infomation-Based Induction Sciences and Machine Learning
Language JPN-ONLY
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English)
Sub Title (in English)
Keyword(1) Neural Networks
Keyword(2) Model Predictive Control
Keyword(3) Musculoskeletal Robot
1st Author's Name
1st Author's Affiliation *(*)
Date 2020-10-21
Paper # IBISML2020-20
Volume (vol) vol.120
Number (no) IBISML-195
Page pp.pp.37-38(IBISML),
#Pages 2
Date of Issue 2020-10-13 (IBISML)