Distilling humanoid locomotion control from offline datasets into deployable policies remains a challenge, as existing methods rely on privileged full-body states that require complex and often unreliable state estimation. We present Sensor-Conditioned Diffusion Policies (SCDP) that enables humanoid locomotion using only onboard sensors, eliminating the need for explicit state estimation. SCDP decouples sensing from supervision through mixed-observation training: diffusion model conditions on sensor histories while being supervised to predict privileged future state-action trajectories, enforcing the model to infer the motion dynamics under partial observability. We further develop restricted denoising, context distribution alignment, and context-aware attention masking to encourage implicit state estimation within the model and to prevent train-deploy mismatch. We validate SCDP on velocity-commanded locomotion and motion reference tracking tasks. In simulation, SCDP achieves near-perfect success on velocity control (99-100%) and 93% tracking success in AMASS test set, performing comparable to privileged baselines while using only onboard sensors. Finally, we deploy the trained policy on a real G1 humanoid at 50 Hz, demonstrating robust real robot locomotion without external sensing or state estimation.
ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion
Mechatronics, Systems and Control Lab (MSC Lab), Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST)（韩国科学技术院机械工程系机电一体化、系统与控制实验室（MSC实验室））；Samsung Electronics, Future Robotics AI Group（三星电子未来机器人人工智能集团）；School of Electrical Engineering, Hanyang University（汉阳大学电气工程学院）；Advanced Robotics Research Center, Korea Institute of Machinery & Materials (KIMM)（韩国机械与材料研究所先进机器人研究中心）
X2-N: A Transformable Wheel-legged Humanoid Robot with Dual-mode Locomotion and Manipulation
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology（香港理工大学电子与计算机工程系）；X-lab Department, Agibot Innovation Company（阿吉博创新公司X实验室）
MASH: Cooperative-Heterogeneous Multi-Agent Reinforcement Learning for Single Humanoid Robot Locomotion
Faculty of Robot Science and Engineering, Northeastern University（机器人科学与工程学院，东北大学）；Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics and School of Intelligence Science and Engineering, the Harbin Institute of Technology Shenzhen（智能变形机制与适应机器人重点实验室和智能科学与工程学院，哈尔滨工业大学深圳）
Trajectory Optimization for Robust Humanoid Locomotion with Sample-Efficient Learning
Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；K. N. Toosi University of Technology（K.N.托西理工大学）；Tandon School of Engineering, New York University（纽约大学坦登工程学院）
HWC-Loco: A Hierarchical Whole-Body Control Approach to Robust Humanoid Locomotion
The Chinese University of Hong Kong (Shenzhen)（香港中文大学（深圳））；Harbin Institute of Technology（哈尔滨工业大学）；DexForce Technology（DexForce科技）；Southeast University（东南大学）
PolygMap: A Perceptive Locomotion Framework for Humanoid Robot Stair Climbing
The Shenzhen Institute of Artificial Intelligence and Robotics for Society（深圳人工智能与机器人社会研究院）；Electronic science and technology, Guangdong University of Technology（广东技术大学电子科学与技术学院）；Leju robotics（乐居机器人）
Cost-Matching Model Predictive Control for Efficient Reinforcement Learning in Humanoid Locomotion
New York University Abu Dhabi (NYUAD)（纽约大学阿布扎比分校）；Georgia Institute of Technology（佐治亚理工学院）；Norwegian University of Science and Technology (NTNU)（挪威科技大学）
StyleLoco: Generative Adversarial Distillation for Natural Humanoid Robot Locomotion
National Key Laboratory of General Artificial Intelligence, BIGAI（通用人工智能国家重点实验室，BIGAI）；School of Control Science and Engineering, Shandong University（山东大学控制科学与工程学院）；Huazhong University of Science and Technology（华中科技大学）
VB-Com: Learning Vision-Blind Composite Humanoid Locomotion Against Deficient Perception
Shanghai AI Laboratory（上海人工智能实验室）；The University of Hong Kong（香港大学）；Shanghai Jiao Tong University（上海交通大学）；Zhejiang University（浙江大学）；The Chinese University of Hong Kong（香港中文大学）
DoublyAware: Dual Planning and Policy Awareness for Temporal Difference Learning in Humanoid Locomotion
University of Texas at Arlington（德克萨斯大学阿灵顿分校）；Intelligent Autonomous Systems Lab（智能自主系统实验室）；German Research Center for AI (DFKI)（德国人工智能研究中心）；Automation & Control Institute (ACIN)（自动化与控制研究所）；Austrian Institute of Technology (AIT) GmbH（奥地利技术研究所）
Adversarial Locomotion and Motion Imitation for Humanoid Policy Learning
Institute of Artificial Intelligence (TeleAI), China Telecom（人工智能研究院（TeleAI），中国电信）；ShanghaiTech University（上海科技大学）；University of Science and Technology of China（中国科学技术大学）；Northwestern Polytechnical University（西北工业大学）；Tsinghua University（清华大学）
Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning
K. N. Toosi University of Technology（K. N. 图西理工大学）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；University of Trento（特伦托大学）；New York University（纽约大学）
TD-GRPC: Temporal Difference Learning with Group Relative Policy Constraint for Humanoid Locomotion
University of Texas at Arlington（德克萨斯大学阿灵顿分校）；VinRobotics；Intelligent Autonomous Systems Lab, TU Darmstadt（图宾根大学智能自主系统实验室）；German Research Center for AI (DFKI)（德国人工智能研究中心）；Automation & Control Institute (ACIN), TU Wien（维也纳技术大学自动化与控制研究所）
Humanoid Locomotion and Manipulation: Current Progress and Challenges in Control, Planning, and Learning
Georgia Institute of Technology（佐治亚理工学院）；The University of Southern California（南加州大学）；Technische Universität München（慕尼黑技术大学）；Google DeepMind（谷歌DeepMind）；The AI Institute（人工智能研究所）；The Institute for Human and Machine Cognition（人机认知研究所）；Duke University（杜克大学）；Kuwait University（科威特大学）；Stanford University（斯坦福大学）；CNRS-University of Montpellier（国家科学研究中心-蒙彼利埃大学）；LIRMM CNRS-AIST Joint Robotics Laboratory（联合机器人实验室）；Simon Fraser University（西蒙弗雷泽大学）；The University of Texas at Austin（德克萨斯大学奥斯汀分校）；NVIDIA（英伟达）；Carnegie Mellon University（卡内基梅隆大学）；Harbin Institute of Technology（哈尔滨工业大学）
Gait-Adaptive Perceptive Humanoid Locomotion with Real-Time Under-Base Terrain Reconstruction
Department of Electronic Engineering and Information Science (EEIS), University of Science and Technology of China（电子工程与信息科学系，中国科学技术大学）；LimX Dynamics（LimX动力学）；Hong Kong University of Science and Technology（香港科技大学）；School of Mechanics Engineering, Harbin Institute of Technology (HIT)（机械工程学院，哈尔滨工业大学）；Department of Computing, The Hong Kong Polytechnic University（计算学院，香港理工大学）；Zhejiang University-University of Illinois Urbana-Champaign Institute (ZJUI)（浙江大学-伊利诺伊大学厄巴纳-香槟分校联合研究所）
