Robot Imitation Learning

Latest papers 647

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

Touch2Robot: Robot Touch in the Human Demonstration Loop
Sep 21, 2026Shengcheng Luo, Xiaoyang Cheng, Hong Ying +6Robotic Data Collection Motion Retargeting
ShanghaiTech University · Beijing Institute for General Artificial Intelligence (BIGAI) · Shanghai Jiao Tong University +1
TACIT: Tactile Contact Supervision for Spatial Attention in Dexterous Manipulation
Sep 21, 2026Yanhou Lai, Fucai Zhu, Ruiqiang Wang +1Contact-Rich Robotic Manipulation Robot Imitation Learning
Graduate School of Information Sciences, Tohoku University, Sendai 980-8579, Japan
Dexterous Robot Manipulation from Human Demonstrations via Contact-Anchored Retargeting and Residual Policy Learning
Sep 21, 2026Zihao Yang, Chengyuan Liu, Yu Zhou +6Dexterous Manipulation Bimanual Robotic Manipulation
DexGEM Lab · Shanghai Jiao Tong University · Tongji University +1
RoboTalk: Learning Multi-Robot Communication and Coordination from Multimodal Demonstrations
Sep 21, 2026Dorian Benhamou Goldfajn, Mason Nakamura, Saaduddin Mahmud +3Multi-Robot Systems Language-Conditioned Robot Manipulation
University of Massachusetts, Amherst, MA, USA. · University of California, Berkeley, CA, USA. · Northeastern University, Boston, MA, USA.
EgoWild2Dex: Learning Dexterous Robotic Manipulation from In-the-Wild Human Experience
Sep 20, 2026Kunyang Lin, Xutao Wen, Jingxi Lin +8Long-Horizon Robotic Manipulation Bimanual Robotic Manipulation
The University of Hong Kong · Kinetix AI
STRIDER: Stepping-Enabled Multi-Gait Hierarchical 3D Loco-Manipulation Framework for Humanoid Robots
Sep 20, 2026Yuanzhuo Li, Wen Zhao, Zhe Yong +6Humanoid Loco-Manipulation Humanoid Robot Locomotion
X-Humanoid, Humanoid Innovation Department
BiRoAD: Learning Shared and Role-Adaptive Representations for Bimanual Manipulation
Sep 20, 2026Yan Shen, Yuchen Liu, Feng Jiang +5Representation Learning Bimanual Robotic Manipulation
CFCS, School of Computer Science, Peking University
Shared Execution-Clock Drifting Policy for Dynamic Precision Manipulation
Sep 20, 2026Zhenchen Dong, Qingran Wu, Jinna Fu +4Dynamic Robotic Manipulation Robot Imitation Learning
The Hong Kong Polytechnic University. · University of California San Diego. · Zhejiang University. +2
Whole-Body UMI: Transferring UMI Manipulation Skills to Humanoid Whole-Body Manipulation via Real-Time Motion Generation
Sep 19, 2026Yuxuan Nai, Leixin Chang, Liangjing Yang +2Whole-Body Robotic Manipulation Robot Motion Generation
Zhejiang University · Hong Kong Embodied AI Lab · Mondo Robotics +1
BEACON: Belief-Enabled Adaptive CONtrol for Imitation Learning under Uncertainty
Sep 19, 2026Moonyoung Lee, Soumojit Bhattacharya, George Kantor +1Robot Imitation Learning Imitation Learning
Carnegie Mellon University, Robotics Institute, Pittsburgh PA 15213, USA
CARF: Contrastive Attraction-Repulsion of Failure-Guided Flow Matching
Sep 18, 2026Shuqi Zhao, Bang Du, Cheng-En Wu +3Robot Policy Learning Learning from Demonstration
GALA: Geometry-Aware Latent Action Modeling for Vision-Language-Action Model Pretraining across Embodiments
Sep 18, 2026Yichen Liu, Puzhen Yuan, Xiang Zhu +2Latent Action Learning Vision-Language-Action Models
Institute for Interdisciplinary Information Sciences, Tsinghua University, China · Shanghai Qi Zhi Institute, China
MAAP: Multi-Agent Active Perception for Collaborative Manipulation
Sep 18, 2026Bruno N. Y. Chen, Li Kang, Heng Zhou +4Active Vision for Robot Manipulation Robotic Manipulation
Carnegie Mellon University · Shanghai Jiao Tong University · University of Science and Technology of China +3
A Sim-to-Real Integration Pipeline for Training and Deployment of Chunk-Based VLA Manipulation Policies
Sep 18, 2026Mathilde Kappel, Clémence Grislain, Mohamed Chetouani +5Sim-to-Real Transfer Robotic Manipulation
Institute of Intelligent Systems and Robotics (ISIR), CNRS, Sorbonne University, Paris, F-75005, France
Skel-WAM: A Hand-Skeleton-Conditioned World Action Model for Human-to-Robot Manipulation Transfer
Sep 18, 2026Zetao Cai, Yaping Li, Yiqun Wang +8Cross-Embodiment Robot Learning World Models for Robotics
The Chinese University of Hong Kong · Shanghai AI Laboratory · Joy Future Academy +1
Learning Distance-Conditioned Object Transport for Humanoid Loco-Manipulation from a Single Motion Clip
Sep 18, 2026Yuhyeon Hwang, Daniel Sungho Jung, YongHyeok Seo +4Humanoid Loco-Manipulation Robot Imitation Learning
Korea Electronics Technology Institute, Republic of Korea. · Seoul National University, Republic of Korea. · Korea University, Republic of Korea.
MicroHookACT: Monocular Microscopic Vision Guided Visuomotor Policy for Flexible Microelectrode Hooking
Sep 18, 2026Yitong Chen, Fangbo Qin, Yang Wang +3Robotic Manipulation Visuomotor Policy Learning
Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China. · State Key Laboratory of Brain Cognition and Brain-Inspired Intelligence Technology, Shanghai 200031, China. +1
Learning Scene-Aware Humanoid Locomotion through 3D Clutter from Immersive Human Demonstrations
Sep 17, 2026Beichen Wang, Tong Xu, Daniel Kosukhin +3Humanoid Robot Locomotion Robot Imitation Learning
George Mason University · New York University
HIL-UMI: Bringing Human-in-the-Loop Post-Training of Vision-Language-Action Models to Universal Manipulation Interface
Sep 17, 2026Zimu Han, Yiming Zeng, Jiyao Zhang +9Interactive Imitation Learning Vision-Language-Action Models
Center on Frontier Computing Studies, School of Computer Science, Peking University, China · Xi’an Jiaotong University, China · National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, China +2
V2-STRep: VLM-Grounded Structured Task Representations for Reusable Robot Skills Acquired from Generated Videos
Sep 17, 2026Yexin Hu, Dongheui LeeZero-Shot Robotic Manipulation Generalization in Robotic Manipulation
Autonomous Systems Lab, Technische Universität Wien (TU Wien), Austria · Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Germany
OmniMimic: Dynamics-completed Motion Augmentation for Multi-style Omnidirectional Quadruped Locomotion
Sep 17, 2026Sheng Wu, Guoqiang Zhao, Zhe Yang +7Robot Imitation Learning Quadruped Locomotion
School of Artificial Intelligence and Robotics, Hunan University, China · China Mobile Group Hunan Company Ltd., China · National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, China
Learning Slope-Adaptive Whole-Body Locomotion for Humanoid Robots in Roofing Construction
Sep 17, 2026Songyang Liu, Shuai LiRL for Robotics Robotic Construction
Ph.D. Student, Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL 32611. · Associate Professor, Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL 32611 (corresponding author).
Universal Navigation Interface: Robot-Free Data for Wheeled Robot Navigation
Sep 17, 2026Sarvesh Prajapati, Ananya Trivedi, Lorena Maria Genua +3Visual Navigation Robotic Data Collection
Institute for Experiential Robotics, Northeastern University, Boston, MA. · Khoury College of Computer Science, Northeastern University, Seattle, WA, USA.
UniExo: Unified Multi-Skill Policies for Musculoskeletal Locomotion and Co-Adaptive Exoskeleton Control
Sep 17, 2026Yifei Yuan, Jakob Wolf, Ghaith Androwis +1Robot Imitation Learning Assistive Robotics
Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA · Kessler Foundation, West Orange, NJ 07052, USA
ReShoot: Generative Visual Domain Randomization of Recorded Robot Demonstrations for Visuomotor Policy Learning
Sep 17, 2026Chiyoung Kim, Min Sung Choi, Jinho Ju +5Domain Randomization Visuomotor Policy Learning
Chung-Ang University, Seoul, Republic of Korea
TacSushi: Tactile-Grounded World-Action Modeling for Dexterous Sushi Manipulation
Sep 17, 2026Haodi Hu, Kaen Kogashi, Toshiaki Koike-AkinoWorld Models for Robotics Contact-Rich Robotic Manipulation
University of Southern California, USA · Mitsubishi Electric Research Laboratories (MERL), USA · Mitsubishi Electric, Japan
ViLoMan: Learning Visual-Proprioceptive Whole-Body Loco-Manipulation Skills for Humanoid Robots
Sep 16, 2026Zejie Tian, Ruibing Hou, Bingpeng Ma +2Humanoid Loco-Manipulation Humanoid Robot Control
State Key Laboratory of AI Safety, Institute of Computing Technology, CAS, China.
In-Context Robot Learning with VLM Agents
Sep 16, 2026Dongzhou Cheng, Taoran Yi, Ye Fang +12Robot Policy Learning ICL for Robotics
Morphi Robot · Shanghai Innovation Institute · Huazhong University of Science and Technology +7
AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation
Sep 16, 2026Jiadi You, Qize Yu, Yue Chen +11World Models for Robotics Cross-Embodiment Robot Learning
The University of Hong Kong · The Hong Kong University of Science and Technology (Guangzhou) · Peking University +3
ULOHA: An Underwater Bimanual Robot System for Robot Learning
Sep 16, 2026Masato Kobayashi, Takeru TsunooriBimanual Robotic Manipulation Visuomotor Policy Learning
The University of Osaka · Kobe University

Sep 21, 2026J/K move · Enter open · S save

Touch2Robot: Robot Touch in the Human Demonstration Loop

Shengcheng Luo, Xiaoyang Cheng, Hong Ying, Xiaoying Zhou+5

ShanghaiTech University · Beijing Institute for General Artificial Intelligence (BIGAI) · Shanghai Jiao Tong University+1

Robotic Data Collection Motion Retargeting Robotic Manipulation Robot Imitation Learning Tactile Sensing for Robotic Manipulation

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Human demonstrations offer a scalable way to collect manipulation data, but their contacts may be unstable or infeasible when transferred to a robot hand. Collecting demonstrations directly on the target robot avoids this mismatch but substantially increases the cost of data collection. To address this trade-off, we present Touch2Robot, a framework that lets humans collect demonstrations while seeing how the target robot hand would contact the object. We capture human hand motion, tactile-glove measurements, and object motion during human manipulation. These recordings guide object-specific RL policies to reproduce the demonstrated object motion while favoring contacts consistent with the recorded human touch. We distill the learned behaviors into a unified real-time retargeter that maps incoming human observations and object geometry to robot hand configurations. During collection, the predicted robot configuration is synchronized with the tracked object pose in simulation to reconstruct robot-object contacts, which are visualized to help the demonstrator adapt subsequent interactions to the target hand. Across four real-world tasks, Touch2Robot improves average real-robot replay completion from 37.9% to 72.1% over visual-only feedback, while reducing the collection time per replay-successful demonstration from 58.6s to 18.2s. Reconstructed target-hand contacts achieve 44.2% F1 against real-robot tactile measurements, and policies trained on Touch2Robot demonstrations improve downstream Diffusion Policy performance by 29.1 percentage points over visual-only feedback. These results show that bringing robot touch into the human demonstration loop improves both the quality and efficiency of scalable dexterous data collection. Project webpage: https://Touch2Robot.github.io/.