Humanoid Robot Control

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Humanoid robot control studies how robots coordinate balance, walking, and whole-body actions such as reaching, carrying, and recovering from pushes. Approaches include model-predictive and whole-body controllers grounded in robot dynamics, reinforcement learning and imitation from human motion, and newer perception- or language-conditioned policies. Researchers test these methods in simulation and on hardware across tasks such as terrain navigation, object handling, teleoperation, and sports. A central challenge is making controllers generalize to new motions, bodies, and contact conditions while remaining stable and safe outside simulation.

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206 papers45 papers in the last four weeks, up 45% on the four weeks before. 0.3% of all new papers.

HybridMimic: Hybrid RL-Centroidal Control for Humanoid Motion Mimicking
Mar 6, 2026Ludwig Chee-Ying Tay, I-Chia Chang, Yan GuHuman-to-Robot Motion Imitation Robotic Control
Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA. · School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
PhysiFlow: Physics-Aware Humanoid Whole-Body VLA via Multi-Brain Latent Flow Matching and Robust Tracking
Mar 5, 2026Weikai Qin, Sichen Wu, Ci Chen +5Humanoid Robot Control Robotic Control
department of Automation Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China · Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education, Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai Jiao Tong University, Shanghai, 200240, China
Interaction-Aware Whole-Body Control for Compliant Object Transport
Mar 4, 2026Hao Zhang, Yves Tseng, Ding Zhao +1Humanoid Robot Control Whole-Body Control
Department of Electrical Engineering, the University of Texas at Arlington, 76010 Arlington, USA · Department of Mechanical Engineering, Carnegie Mellon University, 15213 Pittsburgh, USA
ULTRA: Unified Multimodal Control for Autonomous Humanoid Whole-Body Loco-Manipulation
Mar 3, 2026Xialin He, Sirui Xu, Xinyao Li +4Robotic Control Humanoid Loco-Manipulation
University of Illinois Urbana-Champaign
Rhythm: Learning Interactive Whole-Body Control for Dual Humanoids
Mar 3, 2026Hongjin Chen, Wei Zhang, Pengfei Li +10RL for Robotics Humanoid Robot Control
Fudan University · TARS Robotics · Tsinghua University +3
Scaling Tasks, Not Samples: Mastering Humanoid Control through Multi-Task Model-Based Reinforcement Learning
Mar 2, 2026Shaohuai Liu, Weirui Ye, Yilun Du +1Multi-Task RL Model-Based RL
Texas A&M University · MIT · Harvard University
Spherical Latent Motion Prior for Physics-Based Simulated Humanoid Control
Mar 1, 2026Jing Tan, Weisheng Xu, Xiangrui Jiang +11Robot Motion Generation Humanoid Robot Control
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · University of Oxford, Oxford, United Kingdom
OmniXtreme: Breaking the Generality Barrier in High-Dynamic Humanoid Control
Feb 27, 2026Yunshen Wang, Shaohang Zhu, Peiyuan Zhi +7Humanoid Robot Control Humanoid Motion Tracking
State Key Laboratory of General Artificial Intelligence, Beijing Institute for General Artificial Intelligence (BIGAI) · Joint Laboratory of Embodied AI and Humanoid Robots, BIGAI & Unitree Robotics · Shanghai Jiao Tong University +4
OmniTrack: General Motion Tracking via Physics-Consistent Reference
Feb 27, 2026Yuhan Li, Peiyuan Zhi, Yunshen Wang +6Humanoid Motion Tracking Humanoid Robot Control
Huazhong University of Science and Technology · State Key Lab of General AI, Beijing Institute for General Artificial Intelligence (BIGAI) · Shanghai Jiao Tong University
LessMimic: Long-Horizon Humanoid Interaction with Unified Distance Field Representations
Feb 25, 2026Yutang Lin, Jieming Cui, Yixuan Li +3Humanoid Robot Control Long-Horizon Robotic Manipulation
Iterative Closed-Loop Motion Synthesis for Scaling the Capabilities of Humanoid Control
Feb 25, 2026Weisheng Xu, Qiwei Wu, Jiaxi Zhang +7Humanoid Robot Control Robot Motion Generation
Hong Kong University of Science and Technology (Guangzhou) · University of Oxford
Generalizing from References using a Multi-Task Reference and Goal-Driven RL Framework
Feb 23, 2026Jiashun Wang, M. Eva Mungai, He Li +3Humanoid Robot Control Robot Policy Generalization
RAI Institute · Carnegie Mellon University
Unified Perceptive Fall Safety for Humanoids
Feb 18, 2026Osher Azulay, Zhengjie Xu, Andrew Scheffer +1Humanoid Robot Fall Recovery Humanoid Robot Control
University of Michigan, Ann Arbor
Humanoid Hanoi: Investigating Shared Whole-Body Control for Skill-Based Box Rearrangement
Feb 14, 2026Minku Kim, Kuan-Chia Chen, Aayam Shrestha +3Humanoid Robot Control Whole-Body Control
The authors are with the Collaborative Robotics and Intelligent Systems Institute, Oregon State University, Corvallis, Oregon, 97331, USA
ExtremControl: Low-Latency Humanoid Teleoperation with Scaled Velocity Feedforward
Feb 11, 2026Ziyan Xiong, Lixing Fang, Junyun Huang +3Robot Teleoperation Humanoid Robot Control
UMass Amherst · Carnegie Mellon University · MIT-IBM Watson AI Lab
Learning Human-Like Badminton Skills for Humanoid Robots
Feb 9, 2026Yeke Chen, Shihao Dong, Xiaoyu Ji +12Humanoid Robot Control Robotic RL
Adaptive Robotic Controls Lab (ArcLab), Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China · EngineAI Robotics Technology Co., Ltd., Shenzhen, China
SHARE: Sharing Human Actions across Robot Embodiments through Unified Retargeting and Tracking
Jan 12, 2026Junzhe Xu, Haoyu Zhang, Yunheng Wang +6Human-to-Robot Motion Imitation Cross-Embodiment Robot Learning
JD Explore Academy Beijing, China
Humanoid Whole-Body Badminton via an Annealed Reinforcement Learning Curriculum
Nov 14, 2025Chenhao Liu, Leyun Jiang, Ningyuan Tian +4RL for Robotics Reinforcement Learning
BFM-Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning
Nov 6, 2025Yitang Li, Zhengyi Luo, Tonghe Zhang +10Humanoid Robot Control Behavioral Foundation Models
1Carnegie Mellon University · 2Meta
Thor: Towards Human-Inspired Whole-Body Reactions for Intense Contact-Rich Environments
Oct 30, 2025Gangyang Li, Hongzhe Shi, Qing Shi +5RL for Robotics Humanoid Loco-Manipulation
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology · Beijing Academy of Artificial Intelligence
A Scalable Whole-body Motion Transfer via Implicit Kinodynamic Motion Retargeting
Sep 18, 2025Xingyu Chen, Hanyu Wu, Sikai Wu +7Humanoid Robot Control Synthetic Data Generation for Robotics
1HKUST(GZ) · 4Xiaomi Robotics Lab · 2ETH Zurich +1
Robot Drummer: Learning Rhythmic Skills for Humanoid Drumming
Jul 15, 2025Asad Ali Shahid, Francesco Braghin, Loris RovedaLong-Horizon Robotic Manipulation Robot Skill Learning
IDSIA, SUPSI, Lugano, Switzerland · Department of Mechanical Engineering, Politecnico di Milano, Italy
KungfuBot: Physics-Based Humanoid Whole-Body Control for Learning Highly-Dynamic Skills
Jun 15, 2025Weiji Xie, Jinrui Han, Jiakun Zheng +6Humanoid Robot Control Robot Imitation Learning
Institute of Artificial Intelligence (TeleAI), China Telecom · Shanghai Jiao Tong University · East China University of Science and Technology +2
Bracing for Impact: Robust Humanoid Push Recovery and Locomotion with Reduced Order Models
May 16, 2025Lizhi Yang, Blake Werner, Adrian B. Ghansah +1Humanoid Robot Locomotion Humanoid Robot Control
AMBER Lab at the Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, USA
SHIELD: Safety on Humanoids via CBFs In Expectation on Learned Dynamics
May 16, 2025Lizhi Yang, Blake Werner, Ryan K. Cosner +3Control Barrier Functions Humanoid Robot Control
Mechanical and Civil Engineering, California Institute of Technology · Aerospace Engineering and Engineering Mechanics, UT Austin · Computer Science, Cornell University
Dancing with REEM-C: A robot-to-human physical-social communication study
Aug 9, 2024Marie Charbonneau, Francisco Javier Andrade Chavez, Katja MombaurHumanoid Robot Control Human-Robot Interaction
Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada. · Systems Design, University of Waterloo, 200 University Ave W, Waterloo, ON, N2L 3G1, Canada. · Engineering, Thompson Rivers University, 805 TRU Way, Kamloops, BC, V2C 0C8, Canada. +1

Mar 6, 2026J/K move · Enter open · S save

HybridMimic: Hybrid RL-Centroidal Control for Humanoid Motion Mimicking

Ludwig Chee-Ying Tay, I-Chia Chang, Yan Gu

Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA. · School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.

Human-to-Robot Motion Imitation Robotic Control Humanoid Robot Control RL for Robotics Robot Imitation Learning

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Motion mimicking, i.e., encouraging the control policy to mimic human motion, facilitates the learning of complex tasks via reinforcement learning (RL) for humanoid robots. Although standard RL frameworks demonstrate impressive locomotion agility, they often bypass explicit reasoning about robot dynamics during deployment, which is a design choice that can lead to physically infeasible commands when the robot encounters out-of-distribution environments. By integrating model-based principles, hybrid approaches can improve performance; however, existing methods typically rely on predefined contact timing, limiting their versatility. This paper introduces HybridMimic, a framework in which a learned policy dynamically modulates a centroidal-model-based controller by predicting continuous contact states and desired centroidal velocities. This architecture exploits the physical grounding of centroidal dynamics to generate feedforward torques that remain feasible even under domain shift. Using physics-informed rewards, the policy is trained to efficiently utilize the centroidal controller's optimization by outputting precise control targets and reference torques. Through hardware experiments on the Booster T1 humanoid, HybridMimic reduces the average base position tracking error by 13% compared to a state-of-the-art RL baseline, demonstrating the robustness of dynamics-aware deployment.