Robot Imitation Learning

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172 papers in the last four weeks, up 310% on the four weeks before. 1.0% of all new papers.

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Universal Pose Pretraining for Generalizable Vision-Language-Action Policies
Feb 23, 2026Haitao Lin, Hanyang Yu, Jingshun Huang +5Robot Policy Learning Vision-Language-Action Models
Tencent Robotics X · Futian Laboratory · The Hong Kong University of Science and Technology +2
Human-to-Robot Interaction: Learning from Video Demonstration for Robot Imitation
Feb 22, 2026Thanh Nguyen Canh, Thanh-Tuan Tran, Haolan Zhang +3Learning from Demonstration Robot Imitation Learning
School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, 923-1211, Ishikawa, Japan. · University of Engineering and Technology, Vietnam National University, 10000, Hanoi, Vietnam. · Department of Robotics, Hanyang University, Ansan, 15588, Gyeonggi, Korea.
HeRO: Hierarchical 3D Semantic Representation for Pose-aware Object Manipulation
Feb 21, 2026Chongyang Xu, Shen Cheng, Haipeng Li +3Robotic Manipulation Robot Imitation Learning
College of Computer Science, Sichuan University · Dexmal · School of Information and Communication Engineering, University of Electronic Science and Technology of China
Learning Smooth Time-Varying Linear Policies with an Action Jacobian Penalty
Feb 20, 2026Zhaoming Xie, Kevin Karol, Jessica HodginsRL Control Robot Imitation Learning
Robotics AI Institute, Cambridge, Massachusetts, USA
WHED: A Wearable Hand Exoskeleton for Natural, High-Quality Demonstration Collection
Feb 20, 2026Mingzhang Zhu, Alvin Zhu, Jose Victor S. H. Ramos +9Dexterous Manipulation Robot Imitation Learning
Department of Mechanical and Aerospace Engineering, UCLA, Los Angeles, CA, USA. · Department of Computer Science, UCLA, Los Angeles, CA, USA. · Department of Electrical Engineering, UCLA, Los Angeles, CA, USA.
IRIS: Learning-Driven Task-Specific Cinema Robot Arm for Visuomotor Motion Control
Feb 19, 2026Qilong Cheng, Matthew Mackay, Ali BereyhiRobotic Control Vision-Based Robot Control
Mechanical and Aerospace Eng. Department, New York University · MIE Department, University of Toronto · ECE Department, University of Toronto
MeshMimic: Geometry-Aware Humanoid Motion Learning through 3D Scene Reconstruction
Feb 17, 2026Qiang Zhang, Jiahao Ma, Peiran Liu +20Terrain-Aware Robot Locomotion Robot Imitation Learning
X-Humanoid · The Hong Kong University of Science and Technology (Guangzhou) · The Australian National University +4
Feasibility-aware Imitation Learning from Observation with Multimodal Feedback
Feb 17, 2026Kei Takahashi, Hikaru Sasaki, Takamitsu MatsubaraImitation Learning Robot Imitation Learning
Division of Information Science, Graduate School of Science and Technology, Nara Institute of Science and Technology (NAIST), Ikoma-shi, Nara 630-0192, Japan
BPP: Long-Context Robot Imitation Learning by Focusing on Key History Frames
Feb 16, 2026Max Sobol Mark, Jacky Liang, Maria Attarian +4Robot Imitation Learning Robot Learning
Carnegie Mellon University · Google DeepMind · Princeton University
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
Scalable Dexterous Robot Learning with AR-based Remote Human-Robot Interactions
Feb 7, 2026Yicheng Yang, Ruijiao Li, Lifeng Wang +7Reinforcement Learning Robotic RL
On the Sample Efficiency of Inverse Dynamics Models for Semi-Supervised Imitation Learning
Feb 2, 2026Sacha Morin, Moonsub Byeon, Alexia Jolicoeur-Martineau +1Latent Action Learning Imitation Learning
Département d’informatique et de recherche opérationnelle, Université de Montréal · Mila – Quebec AI Institute · Samsung AI Lab, Montreal +1
HumanX: Toward Agile and Generalizable Humanoid Interaction Skills from Human Videos
Feb 2, 2026Yinhuai Wang, Qihan Zhao, Yuen Fui Lau +6Robot Skill Learning Humanoid Robotics
The Hong Kong University of Science and Technology · Shanghai AI Laboratory
Cross-Modal Visuo-Tactile Representation Learning with Action Chunking Transformers for Contact-Rich Manipulation
Jan 31, 2026Yaohua Liu, Rong Fu, Amir H. Gandomi +2Representation Learning Cross-Modal Representation Learning
Chinese Medicine Guangdong Laboratory, Hengqin, Zhuhai 519031, China · Institute of Collaborative Innovation, University of Macau, Macau 999078, China · Faculty of Engineering & IT, University of Technology Sydney, Ultimo, NSW 2007, Australia +3
CoLA-Flow Policy: Temporally Coherent Imitation Learning via Continuous Latent Action Flow Matching for Robotic Manipulation
Jan 30, 2026Wu Songwei, Jiang Zhiduo, Sun Wandong +4Flow Matching Latent Action Learning
Harbin Institute of Technology, Harbin 150001, China · Honor Device Co., Ltd., Shenzhen, China
OGPO: One-Step Generative Policy Optimization for Real-Time Robot Control
Jan 28, 2026Guowei Zou, Haitao Wang, Hejun Wu +3Robotic Control RL for Robotics
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China · Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou, China
Sim-and-Human Co-training for Data-Efficient and Scene-Generalizable Bimanual Manipulation
Jan 27, 2026Kaipeng Fang, Weiqing Liang, Yuyang Li +5Robot Skill Learning Bimanual Robotic Manipulation
University of Electronic Science and Technology of China · Southwest Jiaotong University · Tongji University +1
SHARE: Sharing Human Actions across Robot Embodiments through Unified Retargeting and Tracking
Jan 12, 2026Junzhe Xu, Haoyu Zhang, Yunheng Wang +6Cross-Embodiment Robot Learning Motion Retargeting
JD Explore Academy Beijing, China
Learning Semantic Atomic Skills for Multi-Task Robotic Manipulation
Dec 20, 2025Yihang Zhu, Weiqing Wang, Shijie Wu +2Long-Horizon Robotic Manipulation Robot Skill Learning
ShanghaiTech University, Shanghai, China · InstAdapt
ISS Policy : Scalable Diffusion Policy with Implicit Scene Supervision
Dec 17, 2025Wenlong Xia, Jinhao Zhang, Ce Zhang +6Robot Skill Learning Visuomotor Policy Learning
[cs.RO]
AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis
Dec 12, 2025Junjie Ye, Rong Xue, Basile Van Hoorick +4Video Diffusion Models Synthetic Data Generation for Robotics
Toyota Research Institute · USC Physical Superintelligence (PSI) Lab
UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations
Dec 12, 2025Tingyu Yuan, Biaoliang Guan, Wen Ye +8Cross-Embodiment Robot Learning Robotic RL
CASIA · UCAS · XJTU +3
Learning Category-level Last-meter Navigation from RGB Demonstrations of a Single-instance
Dec 11, 2025Tzu-Hsien Lee, Fidan Mahmudova, Karthik DesinghRobot Skill Learning Robot Navigation
University of Minnesota, Twin Cities
MILE: A Mechanically Isomorphic Hand Exoskeleton and Visuotactile Robotic Hand for Data Collection in Dexterous Manipulation
Nov 29, 2025Jinda Du, Jieji Ren, Qiaojun Yu +6Robotic Hand Design Dexterous Manipulation
State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. · Shanghai Key Laboratory of Intelligent Robotics, Shanghai Jiao Tong University, Shanghai 200240, China. · Shanghai Artificial Intelligence Laboratory, Shanghai, China. +1
SeFA-Policy: Fast and Accurate Visuomotor Policy Learning with Selective Flow Alignment
Nov 11, 2025Rong Xue, Jiageng Mao, Mingtong Zhang +1Rectified Flow Visuomotor Policy Learning
University of Southern California
PHUMA: Physically Reliable Humanoid Locomotion Dataset
Oct 30, 2025Kyungmin Lee, Sibeen Kim, Youngdo Lee +6Humanoid Robot Locomotion Robot Imitation Learning
KAIST
Few-Shot Demonstration-Driven Task Coordination and Trajectory Execution for Multi-Robot Systems
Oct 17, 2025Taehyeon Kim, Vishnunandan L. N. Venkatesh, Byung-Cheol MinRobot Motion Generation Imitation Learning
Purdue University, West Lafayette, IN, USA · Astemo Americas, Inc., Farmington Hills, MI, USA · Indiana University Bloomington, Bloomington, IN, USA
MM-Nav: Multi-View VLA Model for Robust Visual Navigation via Multi-Expert Learning
Oct 3, 2025Tianyu Xu, Jiawei Chen, Jiazhao Zhang +5Robot Navigation Vision-Language-Action Models
Peking University, Beijing, China · Galbot, Beijing, China · Shanghai Jiao Tong University, Shanghai, China +1
ARMADA: Autonomous Online Failure Detection and Human Shared Control Empower Scalable Real-world Deployment and Adaptation
Oct 2, 2025Wenye Yu, Jun Lv, Zixi Ying +3Robot Policy Adaptation Robot Imitation Learning
Shanghai Jiao Tong University · Shanghai Innovation Institute · Noematrix Ltd.
RTFF: Random-to-Target Fabric Flattening Policy using Dual-Arm Manipulator
Oct 1, 2025Kai Tang, Dipankar Bhattacharya, Hang Xu +3Bimanual Robotic Manipulation Deformable Object Manipulation
Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, Hong Kong SAR, China · Dyson School of Design Engineering, Imperial College London, London, United Kingdom · JD.COM, Shenzhen, China +2

Feb 23, 2026J/K move · Enter open · S save

Universal Pose Pretraining for Generalizable Vision-Language-Action Policies

Haitao Lin, Hanyang Yu, Jingshun Huang, He Zhang+4

Tencent Robotics X · Futian Laboratory · The Hong Kong University of Science and Technology+2

Robot Policy Learning Vision-Language-Action Models Robot Imitation Learning 3D Representation Learning Robot Policy Generalization

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Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level perception with sparse, embodiment-specific action supervision. Since these models typically rely on VLM backbones optimized for Visual Question Answering (VQA), they excel at semantic identification but often overlook subtle 3D state variations that dictate distinct action patterns. To resolve these misalignments, we propose Pose-VLA, a decoupled paradigm that separates VLA training into a pre-training phase for extracting universal 3D spatial priors in a unified camera-centric space, and a post-training phase for efficient embodiment alignment within robot-specific action space. By introducing discrete pose tokens as a universal representation, Pose-VLA seamlessly integrates spatial grounding from diverse 3D datasets with geometry-level trajectories from robotic demonstrations. Our framework follows a two-stage pre-training pipeline, establishing fundamental spatial grounding via poses followed by motion alignment through trajectory supervision. Extensive evaluations demonstrate that Pose-VLA achieves state-of-the-art results on RoboTwin 2.0 with a 79.5% average success rate and competitive performance on LIBERO at 96.0%. Real-world experiments further showcase robust generalization across diverse objects using only 100 demonstrations per task, validating the efficiency of our pre-training paradigm.