Deep Predictive Model Learning with Parametric Bias
Author:
Affiliation:
1. Graduate School of Information Science and Technology, The University of Tokyo
Publisher
The Robotics Society of Japan
Subject
General Medicine
Link
https://www.jstage.jst.go.jp/article/jrsj/40/9/40_40_784/_pdf
Reference25 articles.
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2. 2) D. Tanaka, S. Arnold and K. Yamazaki: “EMD Net: An Encode-Manipulate-Decode Network for Cloth Manipulation,” IEEE Robotics and Automation Letters, vol.3, no.3, pp.1771–1778, 2018.
3. 3) Y. Kuniyoshi and S. Suzuki: Dynamic emergence and adaptation of behavior through embodiment as coupled chaotic field,” Proc. of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.2042–2049, 2004.
4. 4) J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun and M. Hutter: “Learning quadrupedal locomotion over challenging terrain,” Science Robotics, vol.5, no.47, eabc5986, 2020.
5. 5) K. Kawaharazuka, K. Tsuzuki, M. Onitsuka, Y. Asano, K. Okada, K. Kawasaki and M. Inaba: “Object Recognition, Dynamic Contact Simulation, Detection, and Control of the Flexible Musculoskeletal Hand Using a Recurrent Neural Network With Parametric Bias,” IEEE Robotics and Automation Letters, vol.5, no.3, pp.4580–4587, 2020.
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