Robotic Manipulation

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Overview

Robotic manipulation studies how machines use sensing and motion to change objects and environments, from picking and assembly to tool use and handling deformable materials. Approaches combine geometric planning and force or impedance control with imitation learning, reinforcement learning, diffusion policies, and vision-language-action models; world models, memory, tactile feedback, and human-video demonstrations are also used. Methods are tested in simulation and on real robots using suites such as LIBERO, RoboTwin, ManiSkill, and RLBench, across clutter, bimanual coordination, mobile manipulation, and precision contact tasks. A central challenge is turning benchmark performance into safe, reliable long-horizon behavior across new objects, cameras, robot bodies, and real-world dynamics, while limiting data collection and inference costs.

Latest papers

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1,704 papers341 papers in the last four weeks, up 29% on the four weeks before. 2.0% of all new papers.

  1. Now You Feel It, Now You See Me: Digital-Twin-based Teleoperation Interface for Dexterous Manipulation

    Oct 4, 2026Youngchan Shim, Kyutae Lee, JooYun Kim +3Robot TeleoperationHaptic Feedback

    Department of Robotics and Mechatronics Engineering, DGIST, Daegu, Korea · Department of Mechanical Engineering, Seoul National University, Seoul, Korea

  2. GeoBridge-VLA: Geometry-Aware Residual Adaptation for Vision-Language-Action Models

    Oct 4, 2026Hyun Song, Kangmin Kim, Loren Jinsoo Um +4Robotic ManipulationVision-Language-Action Models

    School of Computing, iRASC Lab., Gachon University

  3. ExStereo: Lifting 2D Vision-Language-Action Models to 3D with Explicit Stereo Representations

    Oct 3, 2026I-Chun Arthur Liu, Jason Chen, Gaurav S. Sukhatme +1Vision-Language-Action ModelsRobotic Manipulation

    Viterbi School of Engineering, University of Southern California

  4. PatternDex: Learning Interaction Patterns to Guide Reinforcement Learning of Bimanual Dexterous Manipulation of Articulated Objects

    Oct 3, 2026David Minkwan Kim, Runfa Blark Li, Beckham Po-Ju Lee +2Robotic ManipulationBimanual Robotic Manipulation

    University of California, San Diego

  5. Robot Learning with Visual Predicted Force

    Oct 3, 2026Haonan Chen, Feiyang Wu, Yuxiang Ma +11Robotic ManipulationContact-Rich Robotic Manipulation

    Harvard University, Cambridge, MA, USA. · Massachusetts Institute of Technology, Cambridge, MA, USA. · University of Pennsylvania, Philadelphia, PA, USA. +1

  6. Test-Time Training as Residual Memory for Robot Policies

    Oct 3, 2026Haoxuan Wang, Gengyu Zhang, Ramana Rao Kompella +2Memory-Augmented AgentsRobot Policy Learning

    University of Illinois Chicago · Cisco Research

  7. ACG-WAM: World-Action Modeling via Action-Conditioned Geometric Latent Prediction

    Oct 3, 2026Jiangtao Liu, Zishang Xiang, Yage He +4Action-Conditioned World ModelsVisuomotor Policy Learning

    School of Automation, Beijing Institute of Technology · LimX Dynamics

  8. RoboIRS: Inference-Time Internal Representation Steering for Generalist Robot Policies

    Oct 3, 2026Jiuzhou Lei, Chang Liu, Dayou Li +5Robot Policy GeneralizationTest-Time Adaptation of VLA Models

    J. Mike Walker ’66 Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843, USA · Edwardson School of Industrial Engineering, Purdue University, West Lafayette, IN, USA · Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX 77843, USA +1

  9. AgenticTactileVLA: Contact-Guided Execution-Time Supervision for Generalizable Dexterous Manipulation without VLA Retraining

    Oct 3, 2026Elizaveta Semenyakina, Ivan Snegirev, Mikhail Kiselev +4Robotic ManipulationGeneralization in Robotic Manipulation

    Intelligent Space Robotics Lab, Skolkovo Institute of Science and Technology, Moscow, Russian Federation. · R&D Center, MWS, Moscow, Russian Federation.

  10. Frame-Level Temporal Alignment for Human-to-Robot Visual Adaptation

    Oct 3, 2026Xizhe Zhang, Jingfeng Zhang, Zirun Zhou +1Robot LearningTransfer Learning

    The University of Auckland · Fudan University

  11. Autonomous Droplet Navigation via Model-Based Reinforcement Learning: Zero-Shot Transfer and Emergent Dynamics

    Oct 3, 2026Rajneesh Anand, Mayuresh V. KothareRobotic ManipulationAutonomous Experimentation

    Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA 18015, USA

  12. Grounded in Time: A Multi-Source Dataset and Benchmark for Temporal Grounding in Robotic Manipulation

    Oct 3, 2026Yi Wang, Yang Yang, Guangqi Xu +9Robotic ManipulationRobot Manipulation Datasets

    H.I.-Robot Lab., School of Automation Science and Engineering, South China University of Technology. · Faculty of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, HKSAR. · School of Astronautics, Northwestern Polytechnical University, Xi’an, China. +1

  13. SWAP: Stepwise Action Policy Routing for Vision-Language-Action Models

    Oct 3, 2026Mousumi Das, Aditeya Prajapati, Abrar Anwar +1Robotic ManipulationVision-Language-Action Models

    University of Southern California

  14. SUAVE: Unified Video-Action Models via Masked Diffusion

    Oct 2, 2026Rhythm Syed, Jean Mercat, Sedrick Keh +5Vision-Language-Action ModelsMasked Diffusion Models

    Columbia University, New York, NY, USA. · Toyota Research Institute, Los Altos, CA, USA.

  15. REDIRECT: A 1% Fix for Bad Robot Habits

    Oct 2, 2026Yu Zhang, Jiazhuo Li, Yancong Wei +3Learning from Suboptimal DemonstrationsRobot Policy Adaptation

    Tsinghua University. · University of Michigan.

  16. World Action Learning via Interaction-Centric Spectral Latent Guidance

    Oct 2, 2026Zhiming Liu, Yikun Miao, Ying Chen +7Robot Policy LearningCross-Embodiment Robot Learning

    The Hong Kong University of Science and Technology Hong Kong SAR, China

  17. XGenAct: Geometry-Enhanced World Action Models through Cross-Task Generation

    Oct 2, 2026Tingting Du, Ziyao Wang, Guoheng Sun +1World Action ModelsRobotic Manipulation

    University of Wisconsin–Madison · University of Maryland, College Park

  18. DexJoCo-X: Benchmarking Action Representations for Multi-Hand Dexterous Manipulation

    Oct 2, 2026Xiangwei Jiang, Yao Mu, Lixin Duan +1Action Representation LearningCross-Embodiment Robot Learning

    University of Electronic Science and Technology of China, China. · Shanghai Jiao Tong University, China.

  19. Keeping JEPA World Models Plannable When Little of the Frame Moves

    Oct 2, 2026Florian Strohm, Patrick Wagner, Jannik Schwab +1Language-Conditioned Robot PlanningWorld Model Learning

    Fraunhofer IPA, Stuttgart, Germany · University of Stuttgart, Germany

  20. PointWAM: 3D World Action Modeling for Dexterous Robotic Manipulation

    Oct 2, 2026Chunghyun Park, Beomjun Kim, Seungcheol Park +5Robotic ManipulationEmbodied World Models

    POSTECH · KAIST · RLWRLD +1

  21. ManiPhysicsBench: Physics-Based Assessment of Object Preservation in VLA Manipulation

    Oct 2, 2026Sangwu Park, Yeonjun In, Wonjoong Kim +3Robotic ManipulationSafety Evaluation of VLA Models

    KAIST

  22. Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation

    Oct 2, 2026Xincheng He, Siyu Ma, Chang Yu +5Robot Skill LearningSim-to-Real Transfer

    University of California, Los Angeles · Shanghai Jiao Tong University · University of Utah +1

  23. AdaTempo: Learning Shared Relative Tempo from Demonstrations for Faster Robot Manipulation

    Oct 2, 2026Jiale Cao, Yike Niu, Zhengrong Xue +1Robotic ManipulationRobot Imitation Learning

    Fudan University · Tsinghua University

  24. Rethinking World-Action Model for Compositional and In-Context Robotic Manipulation

    Oct 1, 2026Shukai Gong, Xuanran Zhai, Yintianrun Zhang +16Long-Horizon Robotic ManipulationRobotic Manipulation

    Peking University

  25. NEEDLEWORK: Offline Rewriting of Robot Data with Verified Local Stitches

    Oct 1, 2026Juntao Ren, Yifan Hou, Shuran SongRobot LearningData-Efficient Robot Learning

    Stanford University · NVIDIA

  26. Reconstruct, Practice, Go Real: Guided Self-Improvement for Embodied Agents

    Oct 1, 2026Yen-Jen Wang, Haozhe Jiang, Shuying Deng +7Robot Skill LearningLarge Language Model-Based Robot Planning

    UC Berkeley · Amazon FAR · MIT +1

  27. Watch, Infer, Coordinate: Inferring Robot Partner Constraints for Zero-Shot Coordination

    Oct 1, 2026Suyu Ye, Zheyuan Zhang, Vaishnav Tadiparthi +5Multi-Agent CoordinationMulti-Robot Coordination

    Honda Research Institute USA · Johns Hopkins University

  28. SkeleWAM: Skeleton World-Action Modeling for Efficient Robotic Manipulation

    Oct 1, 2026Juyi Sheng, Hua Wang, Mengyuan LiuWorld Models for RoboticsRobotic Manipulation

    Peking University

  29. Fewer Tokens, Better Action: GPT-6 Astra Robot Agents with 14% Higher Success Rate but 65% Fewer Tokens

    Oct 1, 2026Ruiyang Si, Jianxin Bi, Shunyu Yang +12Vision-Language-Action ModelsTool-Augmented Language Model Agents

    Peking University · National University of Singapore · NVIDIA +1

  30. FlashDexRetarget: Accelerating Dexterous Manipulation Data Generation through Multi-Motion Retargeting

    Oct 1, 2026Kyungmin Lee, Sibeen Kim, Dongyoon Hwang +6RL for RoboticsCross-Embodiment Robot Learning

    KAIST AI · Holiday Robotics