Data-efficient learning of robotic clothing assistance using Bayesian Gaussian process latent variable model-Reference-Cited by-同舟云学术

Data-efficient learning of robotic clothing assistance using Bayesian Gaussian process latent variable model

Published:2019-04-26 Issue:15-16 Volume:33 Page:800-814
ISSN:0169-1864
Container-title:Advanced Robotics
language:en
Short-container-title:Advanced Robotics

Author:

Koganti Nishanth¹^ORCID,Shibata Tomohiro²^ORCID,Tamei Tomoya³,Ikeda Kazushi¹^ORCID

Affiliation:

1. Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan

2. Graduate School of Life Sciences and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

3. Mathematical and Data Science Center, Kobe University, Kobe, Japan

Funder

Cabinet Office, Government of Japan

Publisher

Informa UK Limited

Subject

Computer Science Applications,Hardware and Architecture,Human-Computer Interaction,Software,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/01691864.2019.1610061

Reference50 articles.

1. Reinforcement learning in robotics: A survey

2. Tamei T, Matsubara T, Rai A, et al. Reinforcement learning of clothing assistance with a dual-arm robot. In: IEEE-RAS International Conference on Humanoid Robots (Humanoids). IEEE; 2011. p. 733–738.

3. Titsias MK, Lawrence ND. Bayesian Gaussian process latent variable model. Proceedings of the 13th International Conference on Artificial Intelligence and Statistics; 2010; Sardinia, Italy; Vol. 9. 2010. p. 844–851.

4. Kober J, Peters JR. Policy search for motor primitives in robotics. International Conference on Neural Information Processing Systems; 2009; Vancouver, Canada; p. 849–856.

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