Learning of Balance Controller Considering Changes in Body State for Musculoskeletal Humanoids
Author:
Affiliation:
1. Graduate School of Information Science and Technology, The University of Tokyo,Department of Mechano-Informatics,Tokyo,Japan,113-8656
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9981026/9981028/09981051.pdf?arnumber=9981051
Reference22 articles.
1. Data-Efficient and Safe Learning for Humanoid Locomotion Aided by a Dynamic Balancing Model
2. Solving Rubik's Cube with a Robot Hand;open;ArXiv Preprint,2019
3. Data Efficient Reinforcement Learning for Legged Robots;yang;Proceedings of the 2019 Conference on Robot Learning,0
4. Learning robust perceptive locomotion for quadrupedal robots in the wild
5. Long-Time Self-Body Image Acquisition and Its Application to the Control of Musculoskeletal Structures
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