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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LIDEA: Human-to-Robot Imitation Learning via Implicit Feature Distillation and Explicit Geometry Alignment
Apr 12, 2026Yifu Xu, Bokai Lin, Xinyu Zhan +4Cross-Embodiment Robot Learning Robot Imitation Learning
Shanghai Jiao Tong University · Shanghai Innovation Institute · Noematrix Ltd.
AffordGen: Generating Diverse Demonstrations for Generalizable Object Manipulation with Afford Correspondence
Apr 12, 2026Jiawei Zhang, Kaizhe Hu, Yingqian Huang +3Robotic Manipulation Generalization in Robotic Manipulation
Shanghai Qi Zhi Institute · Tsinghua University · Fudan University +1
MoRI: Mixture of RL and IL Experts for Long-Horizon Manipulation Tasks
Apr 11, 2026Yaohang Xu, Lianjie Ma, Gewei Zuo +3Robotic RL Long-Horizon Robotic Manipulation
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China. · DRAGON Lab, The University of Tokyo, Tokyo, Japan. · School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
ActiveGlasses: Learning Manipulation with Active Vision from Ego-centric Human Demonstration
Apr 9, 2026Yanwen Zou, Chenyang Shi, Wenye Yu +5Active Vision for Robot Manipulation Robot Imitation Learning
Shanghai Jiao Tong University · Shanghai Innovation Institute · Noematrix Ltd.
Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations
Apr 8, 2026Chao Tang, Jiacheng Xu, Haofei Lu +4Robotic Grasping Zero-Shot Robotic Manipulation
Department of Robotics, Perception and Learning, KTH Royal Institute of Technology, Stockholm, Sweden. · Shenzhen Key Laboratory of Robotics and Computer Vision, Southern University of Science and Technology, Shenzhen, China.
HiPolicy: Hierarchical Multi-Frequency Action Chunking for Policy Learning
Apr 7, 2026Jiyao Zhang, Zimu Han, Junhan Wang +7Policy Learning Action Chunking
CFCS, School of CS, PKU · National Key Laboratory for Multimedia Information Processing, School of CS, PKU · XJTU +3
LatentMimic: Terrain-Adaptive Locomotion via Latent Space Imitation
Apr 7, 2026Zhiquan Wang, Yunyu Liu, Dipam Patel +3Terrain-Aware Robot Locomotion Quadruped Locomotion
Department of Computer Science, Purdue University, USA
Learning from Imperfect Demonstrations via Temporal Behavior Tree-Guided Trajectory Repair
Apr 5, 2026Aniruddh G. Puranic, Sebastian Schirmer, John S. Baras +1Robot Imitation Learning RL for Robotics
Institute of Systems Research (ISR), University of Maryland, College Park, United States · DLR German Aerospace Center, Department of Unmanned Aircraft, Braunschweig, Germany
Build on Priors: Vision--Language--Guided Neuro-Symbolic Imitation Learning for Data-Efficient Real-World Robot Manipulation
Apr 4, 2026Pierrick Lorang, Johannes Huemer, Timothy Duggan +3Robot Imitation Learning Robotic Manipulation
Department of Computer Science, Tufts University, Medford, MA, USA · Complex Dynamical Systems, Austrian Institute of Technology GmbH (AIT), Vienna, Austria
Human-Robot Copilot for Data-Efficient Imitation Learning
Apr 4, 2026Rui Yan, Zaitian Gongye, Lars Paulsen +2Imitation Learning Robot Imitation Learning
UC San Diego
Optimizing Neurorobot Policy under Limited Demonstration Data through Preference Regret
Apr 4, 2026Viet Dung Nguyen, Yuhang Song, Anh Nguyen +3Learning from Demonstration Robot Imitation Learning
Rochester Institute of Technology · Advanced Micro Devices, Inc. · University of Liverpool
Tune to Learn: How Controller Gains Shape Robot Policy Learning
Apr 2, 2026Antonia Bronars, Younghyo Park, Pulkit AgrawalRobot Policy Learning Robotic Control
MIT · MIT Improbable AI Lab
Functional Force-Aware Retargeting from Virtual Human Demos to Soft Robot Policies
Apr 1, 2026Uksang Yoo, Mengjia Zhu, Evan Pezent +8Motion Retargeting Robot Imitation Learning
The Robotics Institute, Carnegie Mellon University · Meta Reality Labs
Multi-Camera View Scaling for Data-Efficient Robot Imitation Learning
Apr 1, 2026Yichen Xie, Yixiao Wang, Shuqi Zhao +4Robot Imitation Learning Imitation Learning
UC Berkeley · Lambda, Inc · MIT
Learning Humanoid Navigation from Human Data
Apr 1, 2026Weizhuo Wang, Yanjie Ze, C. Karen Liu +1Robot Navigation Robot Imitation Learning
W. Wang, Y. Ze, C. K. Liu, and M. Kennedy III are with Stanford University, Stanford, CA 94305 USA
Enhancing Policy Learning with World-Action Model
Mar 30, 2026Yuci Han, Alper YilmazRobot Policy Learning World Action Models
Photogrammetry and Computer Vision Lab, The Ohio State University, Columbus, OH 43210, USA.
Active Stereo-Camera Outperforms Multi-Sensor Setup in ACT Imitation Learning for Humanoid Manipulation
Mar 30, 2026Robin Kühn, Moritz Schappler, Thomas Seel +1Robot Imitation Learning Robot Learning
The authors are with the Institute of Mechatronic Systems, Leibniz University Hannover, 30167 Hannover, Germany.
Flip Stunts on Bicycle Robots using Iterative Motion Imitation
Mar 30, 2026Jeonghwan Kim, Shamel Fahmi, Seungeun Rho +2Robot Imitation Learning Imitation Learning
RAI Institute, Cambridge, MA, USA · Georgia Institute of Technology, Atlanta, GA, USA
Liquid Networks with Mixture Density Heads for Efficient Imitation Learning
Mar 28, 2026Nikolaus CorrellImitation Learning Robot Imitation Learning
University of Colorado Boulder
Partial Motion Imitation for Learning Cart Pushing with Legged Manipulators
Mar 27, 2026Mili Das, Morgan Byrd, Donghoon Baek +1Legged Robotics Imitation Learning
Georgia Institute of Technology, Atlanta, GA, 30308, USA
Addressing Ambiguity in Imitation Learning through Product of Experts based Negative Feedback
Mar 27, 2026John Bateman, Andy M. Tyrrell, Jihong ZhuImitation Learning Robot Imitation Learning
University of York
Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories
Mar 26, 2026Yiyuan Pan, Xusheng Luo, Hanjiang Hu +2Visuomotor Policy Learning Neurosymbolic Learning
Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
Towards Embodied AI with MuscleMimic: Unlocking full-body musculoskeletal motor learning at scale
Mar 26, 2026Chengkun Li, Cheryl Wang, Bianca Ziliotto +4Robotics Simulation Robot Imitation Learning
EPFL, Switzerland · McGill University, Canada · Feil & Oberfeld CRIR-Jewish Rehabilitation Hospital Research Center, Canada +1
UniDex: A Robot Foundation Suite for Universal Dexterous Hand Control from Egocentric Human Videos
Mar 23, 2026Gu Zhang, Qicheng Xu, Haozhe Zhang +16Robotic Manipulation Cross-Embodiment Robot Learning
Tsinghua University · Shanghai Qizhi Institute · Sun Yat-sen University +1
ATG-MoE: Autoregressive trajectory generation with mixture-of-experts for assembly skill learning
Mar 19, 2026Weihang Huang, Chaoran Zhang, Xiaoxin Deng +4Robotic Assembly Multi-Task Robotic Manipulation
Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China · Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
Generative Control as Optimization: Time Unconditional Flow Matching for Adaptive and Robust Robotic Control
Mar 18, 2026Zunzhe Zhang, Runhan Huang, Yicheng Liu +3Robotic Control Robot Imitation Learning
Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China · Galaxea Inc., Beijing, China · Department of Computer Science, Princeton University, New Jersey, US
VolumeDP: Modeling Volumetric Representation for Manipulation Policy Learning
Mar 18, 2026Tianxing Zhou, Feiyang Xue, Zhangchen Ye +3Visuomotor Policy Learning Robotic Manipulation
1IIIS, Tsinghua University · 2Galaxea AI
DexEXO: A Wearability-First Dexterous Exoskeleton for Operator-Agnostic Demonstration and Learning
Mar 18, 2026Alvin Zhu, Mingzhang Zhu, Beom Jun Kim +10Cross-Embodiment Robot Learning Robotic Hand Design
Department of Computer Science, UCLA, Los Angeles, CA, USA. · Department of Electrical and Computer Engineering, UCLA, Los Angeles, CA, USA. · Department of Mechanical and Aerospace Engineering, UCLA, Los Angeles, CA, USA.
Influence of Gripper Design on Human Demonstration Quality for Robot Learning
Mar 17, 2026Gina L. Georgadarellis, Natalija Beslic, Seonhun Lee +2Robotics Robotic Manipulation
Department of Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA 01003 USA · Elaine Marieb Center for Nursing and Engineering Innovation, University of Massachusetts Amherst, Amherst, MA 01003 USA · Center for Personalized Health Monitoring, Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA 01003
ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors
Mar 16, 2026Zifan Xu, Ran Gong, Maria Vittoria Minniti +10Long-Horizon Robotic Manipulation Robot Skill Learning
Robotics and AI Institute · University of Texas at Austin · Sony AI

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LIDEA: Human-to-Robot Imitation Learning via Implicit Feature Distillation and Explicit Geometry Alignment

Yifu Xu, Bokai Lin, Xinyu Zhan, Hongjie Fang+3

Shanghai Jiao Tong University · Shanghai Innovation Institute · Noematrix Ltd.

Cross-Embodiment Robot Learning Robot Imitation Learning Data-Efficient Robot Learning Generalization in Robotic Manipulation Knowledge Distillation

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Scaling up robot learning is hindered by the scarcity of robotic demonstrations, whereas human videos offer a vast, untapped source of interaction data. However, bridging the embodiment gap between human hands and robot arms remains a critical challenge. Existing cross-embodiment transfer strategies typically rely on visual editing, but they often introduce visual artifacts due to intrinsic discrepancies in visual appearance and 3D geometry. To address these limitations, we introduce LIDEA (Implicit Feature Distillation and Explicit Geometric Alignment), an imitation learning framework in which policy learning benefits from human demonstrations. In the 2D visual domain, LIDEA employs a dual-stage transitive distillation pipeline that aligns human and robot representations in a shared latent space. In the 3D geometric domain, we propose an embodiment-agnostic alignment strategy that explicitly decouples embodiment from interaction geometry, ensuring consistent 3D-aware perception. Extensive experiments empirically validate LIDEA from two perspectives: data efficiency and OOD robustness. Results show that human data substitutes up to 80% of costly robot demonstrations, and the framework successfully transfers unseen patterns from human videos for out-of-distribution generalization.