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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CoDance: Learning Reactive and Compliant Human-Humanoid Interaction from Video
Oct 4, 2026Zhuoqun Chen, Shucheng Jia, Boyuan ChenRobotic Control Humanoid Robot Locomotion
Duke University
LEAP: Making Privileged Geometry Supervision Effective for Visuomotor Learning
Oct 4, 2026Han Fang, Yunpeng Jiang, Jianshu Hu +6Visuomotor Policy Learning Robot Imitation Learning
Global College, Shanghai Jiao Tong University Shanghai, China · Shanghai Institute of Physical Intelligence and Robotics (PAIR) Shanghai, China · East China University of Science and Technology Shanghai, China +2
Recursive Self-Improvement of Visuomotor Policies through Local Recovery Supervision
Oct 4, 2026Yuzhi Zhang, Xinyu Liu, Yu ZhangRobot Failure Recovery Visuomotor Policy Learning
Beihang University
DreamFormer: Dream Imitation with a Transformer World Model for Language-Conditioned Robotic Manipulation
Oct 3, 2026Mostafa Kotb, Cornelius Weber, Muhammad Burhan Hafez +1Language-Conditioned Robot Manipulation Robot Imitation Learning
Knowledge Technology Group, Department of Informatics, University of Hamburg, 20146 Hamburg, Germany · Mathematics Department, Faculty of Science, Aswan University, 81528 Aswan, Egypt · School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
TacOT: Learning Contact-Rich Dexterous Manipulation from Human Demonstrations via Tactile-Guided Optimal Transport
Oct 3, 2026Xingting Li, Yifan Han, Zijian Lin +4Contact-Rich Robotic Manipulation Robot Imitation Learning
Shenzhen Ubiquitous Data Enabling Key Lab, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China. · School of Artificial Intelligence, Shanghai Jiao Tong University, Shanghai 200030, China. · Xspark AI, Shenzhen, China. +1
Reward-DAgger: Robot-Gated Interactive Imitation Learning with General-Purpose Progress-Based Reward Models
Oct 2, 2026Ryan Li, Yigit Korkmaz, Erdem BıyıkRobot Imitation Learning Interactive Imitation Learning
Department of Mathematics, University of Southern California · Thomas Lord Department of Computer Science, University of Southern California
REDIRECT: A 1% Fix for Bad Robot Habits
Oct 2, 2026Yu Zhang, Jiazhuo Li, Yancong Wei +3Robot Policy Adaptation Learning from Demonstration
Tsinghua University. · University of Michigan.
Bridging Frontier Reasoning and Robot Execution: From Autonomous Demonstration Generation to Dense Language Supervision
Oct 2, 2026Bosung Kim, Alexander Trevithick, Ruiyi Wang +1Robot Learning Language-Conditioned Robot Manipulation
University of California, San Diego · NVIDIA
World Action Learning via Interaction-Centric Spectral Latent Guidance
Oct 2, 2026Zhiming Liu, Yikun Miao, Ying Chen +7Robot Policy Learning Cross-Embodiment Robot Learning
The Hong Kong University of Science and Technology Hong Kong SAR, China
KungfuAthleteBot: learning high-dynamic humanoid motion from video with unified robust recovery
Oct 2, 2026Zhongxiang Lei, Lulu Cao, Xuyang Wang +3RL for Robotics Robot Imitation Learning
Beijing Institute of Technology · Equal contribution · QIYUAN Lab
Equivariant Visual-Tactile Diffusion Policy for Contact-Rich Manipulation
Oct 2, 2026Lik Hang Kenny Wong, Yiyao Ma, Xiu-Shen Wei +5Robot Imitation Learning Robot Learning
Department of Computer Science and Engineering, The Chinese University of Hong Kong · School of Computer Science and Engineering, Southeast University
PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation
Oct 2, 2026Chunghyun Park, Beomjun Kim, Seungcheol Park +5Robotic Manipulation Embodied World Models
POSTECH · KAIST · RLWRLD +1
Register-Routed Delayed Fusion: Rewiring Shortcut-Prone Observation Fusion in Visuomotor Imitation
Oct 2, 2026Jieting Long, Weidong Cai, Weiming ZhiVisuomotor Policy Learning Robot Imitation Learning
School of Computer Science, The University of Sydney, Australia.
AdaTempo: Learning Shared Relative Tempo from Demonstrations for Faster Robot Manipulation
Oct 2, 2026Jiale Cao, Yike Niu, Zhengrong Xue +1Robotic Manipulation Robot Imitation Learning
Fudan University · Tsinghua University
FlashDexRetarget: Accelerating Dexterous Manipulation Data Generation through Multi-Motion Retargeting
Oct 1, 2026Kyungmin Lee, Sibeen Kim, Dongyoon Hwang +6RL for Robotics Cross-Embodiment Robot Learning
KAIST AI · Holiday Robotics
Interaction-Stiffness-Guided Basis Allocation in Dynamic Movement Primitives for Efficient Skill Transfer
Oct 1, 2026Chan Xu, Silu Chen, Dehao Wang +6Robot Motion Generation Robot Imitation Learning
Zhejiang Key Laboratory of Precision Actuation and Intelligent Robotics, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China · University of Chinese Academy of Sciences, Beijing 100049, China · Department of Computing, The Hong Kong Polytechnic University, HKSAR, China
Recova: Agent-Guided Failure Recovery for Autonomous Robotic Manipulation
Oct 1, 2026Isabella Liu, An-Chieh Cheng, Johan Bjorck +6Robot Failure Recovery Human-in-the-Loop AI
University of California, San Diego · NVIDIA · University of Texas at Austin
Getting Out and Getting Back: World and Behavior Grounding in Real2Sim2Real Co-Training
Sep 30, 2026Samuel Liu, Youngsun Kim, Martin Matak +1Sim-to-Real Transfer Synthetic Data Generation for Robotics
University of Cambridge · Industrial Next
Does Continual Imitation Learning Remain Grounded? A Language-Perturbed Benchmark for Robotic Task Retention
Sep 30, 2026Siddeshwar Raghavan, Ziqin Yuan, Fengqing Zhu +1Robot Imitation Learning
Department of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA. · Department of Computer and Information Technology,Purdue University, West Lafayette, IN, USA. · Computer Science and Intelligent Systems Engineering, Indiana University Bloomington, IN, USA.
Ego4WAM: What Matters When Scaling Egocentric Human Data for Robot Learning?
Sep 30, 2026Zhihao Sun, Liu Liu, Xinjiang Wang +6Data-Efficient Robot Learning Robot Imitation Learning
Institute of Trustworthy Embodied AI, Fudan University · Horizon Robotics · Huazhong University of Science & Technology +1
IronMind: Scaling Humanoid Dexterous Manipulation via Camera-Space Ego-Centric Pretraining
Sep 30, 2026Huimin Pan, Yufan Ren, Kunpeng Song +16Cross-Embodiment Robot Learning Vision-Language-Action Models
World Model Team, XPENG Robotics
Video2SwimFish: An Automated Pipeline for Reconstructing Controllable Fish Models and Biological Locomotion from Real Fish Videos
Sep 30, 2026Hangong Chen, Linfeng Cheng, Tahsin Zaman Jilan +4Underwater 3D Reconstruction Robot Locomotion
Department of Computer Science, North Carolina A&T State University · Department of Computer Science, University of Maryland, College Park
Plan-Conditioned Imitation for Robust Object Retrieval under Self-Occlusion in Dense Clutter
Sep 30, 2026Kowndinya Boyalakuntla, Ajinkya Pawar, Abdeslam Boularias +1Imitation Learning Robotic Manipulation
Rutgers University · Indian Institute of Technology Bombay, India
Memorize, Adapt, Ignore: Diagnosing Robot Learning Mechanisms under Training Data Variation
Sep 29, 2026Ke Zhang, Danica J. Sutherland, Chao LiuDomain Randomization Robot Policy Adaptation
PRIME Robotics Lab, Department of Mechanical Engineering, The University of British Columbia · Department of Computer Science, University of British Columbia · Alberta Machine Intelligence Institute
Counterfactual Video Generation Enables Scalable Humanoid Loco-Manipulation
Sep 29, 2026Zihan Wang, Zhen Wu, Pieter Abbeel +6HOI Generation Humanoid Loco-Manipulation
Amazon FAR · UC Berkeley · Stanford +1
BlenDAgger: Blended Shared Control for Interactive Imitation Learning
Sep 29, 2026Cailyn Smith, Geoffrey Sun, Henny Admoni +1Robotic Control Robotic Manipulation
The Robotics Institute, School of Computer Science Carnegie Mellon University Pittsburgh, USA · School of Computer Science Carnegie Mellon University Pittsburgh, USA
Wrench-ACT: Enhancing Robot Policies for Contact Rich Behavior Using Direct Wrench Control
Sep 29, 2026Johannes Hechtl, Yannik Blei, Simon Ball +5Contact-Rich Robotic Manipulation Force-Controlled Robotic Manipulation
Siemens Research and Predevelopment · Department of Computer Science and Artificial Intelligence, University of Technology Nuremberg, Germany
Direct Experience World-Model Optimization: Learning the World Beyond Action Imitation
Sep 29, 2026Xiangcheng Zhan, Zirui Chen, Yicheng Zhao +2Test-Time Adaptation World Model Learning
Harbin Institute of Technology · Dalian University of Technology · Southern University of Science and Technology
EgoHumanoid-V2: Human-to-Humanoid Transfer of Coordinated Whole-Body Skills for Loco-Manipulation
Sep 29, 2026Jin Chen, Yiming Jiang, Chongyang Xu +8Humanoid Loco-Manipulation Whole-Body Robotic Manipulation
OpenDriveLab at The University of Hong Kong · Alibaba Group · Shanghai Innovation Institute +4
Multi-Granularity Language-Guided Imitation Learning via Instruction Decomposition
Sep 29, 2026Yi-Pei Chiu, Wei-Ta ChuLanguage-Conditioned Robot Manipulation Imitation Learning
National Cheng Kung University, Taiwan

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CoDance: Learning Reactive and Compliant Human-Humanoid Interaction from Video

Zhuoqun Chen, Shucheng Jia, Boyuan Chen

Duke University

Robotic Control Humanoid Robot Locomotion Human-Robot Collaboration Robot Imitation Learning Human-Robot Interaction

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Partnered human-humanoid interaction couples locomotion with continuous physical contact. A humanoid needs to coordinate with a person's motion while responding to interaction forces and maintaining stable and natural movement. We present CoDance, a framework for learning reactive and compliant human-humanoid interaction from video. We study partnered dancing as a challenging instantiation, where a humanoid coordinates its footsteps with a moving partner and maintains continuous two-hand contact. Given a single video of two human dancers, CoDance retargets their motions into a robot reference and a moving partner. We introduce a multi-link compliance augmentation that transforms the kinematic demonstration into force-aware training data by adapting the robot reference under structured forces at both hands. Policies trained on this data follow the observed partner while preserving the demonstrated locomotion style and responding compliantly to physical interaction. In simulation, the policies adapt their footsteps to changes in the partner and reproduce approximately 80% of the wrist displacement encoded by the augmented demonstrations. On a physical humanoid, CoDance enables sustained two-hand dancing with a human partner including repeated transitions between forward and backward motions.