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The human body demonstrates exceptional motor capabilities-such as standing steadily on one foot or performing a high kick with the leg raised over 1.5 meters-both requiring precise balance control.
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B. Stephens · 2007
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Multiple balance strategies from one optimization criterion
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Team ihmc’s lessons learned from the darpa robotics challenge trials
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Preparing for the unknown: Learning a universal policy with online system identification
W. Yu, J. Tan, C. K. Liu, and G. Turk · 2017
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Proximal policy optimization algorithms
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Learning whole-body motor skills for humanoids
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Fast model identification via physics engines for data-efficient policy search
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Hover: Versatile neural whole-body controller for humanoid robots
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Expressive whole-body control for humanoid robots
X. Cheng, Y. Ji, J. Chen, R. Yang, G. Yang, and X. Wang · 2024
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Exbody2: Advanced expressive humanoid whole-body control
M. Ji, X. Peng, F. Liu, J. Li, G. Yang, X. Cheng, and X. Wang · 2024
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Wham: Reconstructing world-grounded humans with accurate 3d motion
S. Shin, J. Kim, E. Halilaj, and M. J. Black · 2024
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Tram: Global trajectory and motion of 3d humans from in-the-wild videos
Y. Wang, Z. Wang, L. Liu, and K. Daniilidis · 2024
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Sim-to-real transfer of robotic control with dynamics randomization
X. B. Peng, M. Andrychowicz, W. Zaremba, and P. Abbeel · 2018
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Domain randomization and generative models for robotic grasping
J. Tobin, L. Biewald, R. Duan, M. Andrychowicz, A. Handa, V. Kumar, B. McGrew, A. Ray, J. Schneider, P. Welinder, et al · 2018
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Using deep reinforcement learning to learn high-level policies on the atrias biped
T. Li, H. Geyer, C. G. Atkeson, and A. Rai · 2019
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Sim-to-real transfer for biped locomotion
W. Yu, V. C. Kumar, G. Turk, and C. K. Liu · 2019
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Tunenet: One-shot residual tuning for system identification and sim-to-real robot task transfer
A. Allevato, E. S. Short, M. Pryor, and A. Thomaz · 2020
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Real–sim–real transfer for real-world robot control policy learning with deep reinforcement learning
N. Liu, Y. Cai, T. Lu, R. Wang, and S. Wang · 2020
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Active domain randomization
B. Mehta, M. Diaz, F. Golemo, C. J. Pal, and L. Paull · 2020
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Advancing humanoid locomotion: Mastering challenging terrains with denoising world model learning
X. Gu, Y.-J. Wang, X. Zhu, C. Shi, Y. Guo, Y. Liu, and J. Chen · 2024
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Berkeley humanoid: A research platform for learning-based control
Q. Liao, B. Zhang, X. Huang, X. Huang, Z. Li, and K. Sreenath · 2024
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Whole-body humanoid robot locomotion with human reference
Q. Zhang, P. Cui, D. Yan, J. Sun, Y. Duan, G. Han, W. Zhao, W. Zhang, Y. Guo, A. Zhang, et al · 2024
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Learning smooth humanoid locomotion through lipschitz-constrained policies
Z. Chen, X. He, Y.-J. Wang, Q. Liao, Y. Ze, Z. Li, S. S. Sastry, J. Wu, K. Sreenath, S. Gupta, et al · 2024
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Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control
Z. Li, X. B. Peng, P. Abbeel, S. Levine, G. Berseth, and K. Sreenath · 2024
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Learning humanoid locomotion with perceptive internal model
J. Long, J. Ren, M. Shi, Z. Wang, T. Huang, P. Luo, and J. Pang · 2024
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Reconciling reality through simulation: A real-to-sim-to-real approach for robust manipulation
M. Torne, A. Simeonov, Z. Li, A. Chan, T. Chen, A. Gupta, and P. Agrawal · 2024
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Domain randomization for sim2real transfer of automatically generated grasping datasets
J. Huber, F. Hélénon, H. Watrelot, F. B. Amar, and S. Doncieux · 2024
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Asap: Aligning simulation and real-world physics for learning agile humanoid whole-body skills
T. He, J. Gao, W. Xiao, Y. Zhang, Z. Wang, J. Wang, Z. Luo, G. He, N. Sobanbabu, C. Pan, Z. Yi, G. Qu, K. Kitani, J. Hodgins, L. J. Fan, Y. Zhu, C. Liu, and G. Shi · 2025
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X. He, R. Dong, Z. Chen, and S. Gupta · 2025
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Learning humanoid standing-up control across diverse postures
T. Huang, J. Ren, H. Wang, Z. Wang, Q. Ben, M. Wen, X. Chen, J. Li, and J. Pang · 2025
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Embrace collisions: Humanoid shadowing for deployable contact-agnostics motions
Z. Zhuang and H. Zhao · 2025
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Homie: Humanoid loco-manipulation with isomorphic exoskeleton cockpit
Q. Ben, F. Jia, J. Zeng, J. Dong, D. Lin, and J. Pang · 2025
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Sim-to-real reinforcement learning for vision-based dexterous manipulation on humanoids
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