Robot Policy Learning

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Overview

Robot policy learning studies how robots can turn camera, depth, tactile, and proprioceptive inputs into actions for tasks such as manipulation, locomotion, and navigation. Common approaches include behavior cloning from demonstrations, reinforcement learning in simulation or on hardware, and diffusion, flow-matching, or vision-language-action policies that generate action sequences; world models and hierarchical planners can add foresight and long-horizon structure. Researchers evaluate these methods in simulation suites such as LIBERO, CALVIN, RoboTwin, and navigation benchmarks, as well as on physical robots, with growing attention to memory, contact, safety, and recovery from failure. A central tension is how to make policies generalize across tasks, robots, and changing conditions while remaining data-efficient, reactive, reliable, and fast enough to deploy.

Latest papers

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377 papers85 papers in the last four weeks, up 47% on the four weeks before. 0.5% of all new papers.

  1. ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation

    Apr 15, 2026Jingjing Qian, Zeyuan He, Chen Shi +2Robotic Spatial MemoryLong-Horizon Robotic Manipulation

    The Chinese University of Hong Kong, Shenzhen · LiAuto Inc.

  2. ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation

    Apr 13, 2026Yiran Qin, Jiahua Ma, Li Kang +11Synthetic Data Generation for RoboticsRobotics Simulation

    CUHK-Shenzhen · University of Oxford · Sun Yat-sen University +4

  3. Rectified Schrödinger Bridge Matching for Few-Step Visual Navigation

    Apr 7, 2026Wuyang Luan, Junhui Li, Weiguang Zhao +3Schrödinger BridgesRobot Policy Learning

    School of Artificial Intelligence, Jilin University, Changchun 130012, China · College of Computer Science, Chongqing University, Chongqing 400044, China · Department of Computer Science, University of Liverpool, Liverpool L69 3BX, UK +1

  4. Multi-Robot Multi-Queue Control via Exhaustive Assignment Actor-Critic Learning

    Apr 4, 2026Mohammad Merati, H. M. Sabbir Ahmad, Wenchao Li +1Multi-Robot Task AllocationRobot Policy Learning

    Divisions of Systems Engineering, Boston University, 8 St Mary’s St, Boston, MA 02215, United States. · Department of Electrical and Computer Engineering, Boston University, 8 St Mary’s St, Boston, MA 02215, United States.

  5. Tune to Learn: How Controller Gains Shape Robot Policy Learning

    Apr 2, 2026Antonia Bronars, Younghyo Park, Pulkit AgrawalRobot Policy LearningRobotic Control

    MIT · MIT Improbable AI Lab

  6. Efficient Camera Pose Augmentation for View Generalization in Robotic Policy Learning

    Mar 31, 2026Sen Wang, Huaiyi Dong, Jingyi Tian +7Robot Policy GeneralizationRobot Policy Learning

    Xi’an Jiaotong University, Noah’s Ark Lab

  7. Enhancing Policy Learning with World-Action Model

    Mar 30, 2026Yuci Han, Alper YilmazRobot Policy LearningWorld Action Models

    Photogrammetry and Computer Vision Lab, The Ohio State University, Columbus, OH 43210, USA.

  8. Policy-Guided World Model Planning for Language-Conditioned Visual Navigation

    Mar 26, 2026Amirhosein Chahe, Lifeng ZhouEmbodied NavigationVision-Language Navigation

    Drexel University Philadelphia PA 19104, USA

  9. Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation

    Mar 26, 2026Roman Küble, Marco Hüller, Mrunmai Phatak +2Robotic RLScene Graph Generation

    Organic Computing Group · University of Augsburg, Am Technologiezentrum 8, Augsburg, Germany · Machine Learning and Computer Vision Group

  10. Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning

    Mar 25, 2026Yude Li, Zhexuan Zhou, Huizhe Li +6Multi-Agent SystemsMulti-Robot Coordination

    The authors are with the School of Intelligence Science and Engineering, the Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics, and the Shenzhen Key Lab for Advanced Motion Control and Modern Automation Equipments, Harbin Institute of Technology, Shenzhen, Guangdong 518055, China

  11. VersualRL: Closed-Loop Verbal Reinforcement Learning with Visual Execution Feedback for Task-Level Robot Planning

    Mar 23, 2026Dmitrii Plotnikov, Iaroslav Kolomiets, Dmitrii Maliukov +9Robot Policy LearningLarge Language Model-Based Robot Planning

    The authors are with the Intelligent Space Robotics Laboratory, Skolkovo Institute of Science and Technology.

  12. Speedup Patch: Learning a Plug-and-Play Policy to Accelerate Embodied Manipulation

    Mar 21, 2026Zhichao Wu, Junyin Ye, Zhilong Zhang +6Robot Policy LearningRobotic Manipulation

    National Key Laboratory for Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China · Mila-Quebec AI Institute & Université de Montréal, Canada

  13. Articulated-Body Dynamics Network: Dynamics-Grounded Prior for Robot Learning

    Mar 19, 2026Sangwoo Shin, Kunzhao Ren, Xiaobin Xiong +1Robot Policy LearningRobot Learning

    University of Wisconsin–Madison. · Shanghai Innovation Institute (SII).

  14. MemoAct: Atkinson-Shiffrin-Inspired Hierarchical Memory-Augmented Policy for Robotic Manipulation

    Mar 19, 2026Liufan Tan, Jiale Li, Gangshan JingMemory-Augmented AgentsRobot Policy Learning

  15. REAL: Robust Extreme Agility via Spatio-Temporal Policy Learning and Physics-Guided Filtering

    Mar 18, 2026Jialong Liu, Dehan Shen, Yanbo Wen +2Robot Policy LearningRobot Locomotion

    PEAK-Lab, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 511453, China.

  16. SmallSatSim: A GPU-Accelerated Microgravity Robotics Toolkit for Planning, Control, and Policy Learning

    Mar 15, 2026David Schwartz, Alexander Hansson, Sabrina Bodmer +3Robotics SimulationSpace Robotics

    ETH Zürich, Rämistrasse 101, 8092 Zürich, Switzerland · Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91011, USA · University of Michigan, 500 South State Street, Ann Arbor, MI 48109, USA +1

  17. Pixel-level Scene Understanding in One Token: Visual States Need What-is-Where Composition

    Mar 14, 2026Seokmin Lee, Yunghee Lee, Byeonghyun Pak +1State Representation LearningSelf-Supervised Visual Representation Learning

    Agency for Defense Development

  18. Prepare to Turn: Learning Anticipatory Maneuvering for Fast Sequential Quadrupedal Navigation

    Mar 13, 2026Zunzhi You, Yunke Wang, Haolan Guo +1Robot Policy LearningRobot Navigation

    All authors are with School of Computer Science, University of Sydney.

  19. FLUX: Accelerating Cross-Embodiment Generative Navigation Policies via Rectified Flow and Static-to-Dynamic Learning

    Mar 13, 2026Zeying Gong, Yangyi Zhong, Yiyi Ding +6Robot Navigation BenchmarksRobot Policy Learning

    The Hong Kong University of Science and Technology (Guangzhou) · The Hong Kong University of Science and Technology · National University of Singapore

  20. Ada3Drift: Adaptive Training-Time Drifting for One-Step 3D Visuomotor Robotic Manipulation

    Mar 12, 2026Chongyang Xu, Yixian Zou, Tianyu Yang +4Robot Policy LearningRobot Skill Learning

    College of Computer Science, Sichuan University, Chengdu, China · School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China

  21. From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning

    Mar 10, 2026Zhanyi Sun, Shuran SongRL for RoboticsRobot Policy Learning

    1Stanford University.

  22. Quality over Quantity: Demonstration Curation via Influence Functions for Data-Centric Robot Learning

    Mar 10, 2026Haeone Lee, Taywon Min, Junsu Kim +4Training Data CurationData-Efficient Robot Learning

    KAIST · University of California, Berkeley · New York University

  23. OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies

    Mar 9, 2026Yunzhou Song, Long Le, Yong-Hyun Park +7Robot Policy LearningVision-Language-Action Models

    University of Pennsylvania

  24. 3PoinTr: From Human Videos to Robot Policies with 3D Point-Track Plans

    Mar 9, 2026Adam Hung, Bardienus Pieter Duisterhof, Jeffrey IchnowskiHuman-to-Robot Motion ImitationRobot Policy Learning

    Carnegie Mellon University

  25. VORL-EXPLORE: A Hybrid Learning Planning Approach to Multi-Robot Exploration in Dynamic Environments

    Mar 9, 2026Ning Liu, Sen Shen, Zheng Li +4Multi-Robot ExplorationMulti-Robot Motion Planning

    The University of Western Australia · The Chinese University of Hong Kong · Karlsruhe Institute of Technology +1

  26. RoboRouter: Training-Free Policy Routing for Robotic Manipulation

    Mar 9, 2026Yiteng Chen, Zhe Cao, Hongjia Ren +9Robot Policy LearningRobotic Manipulation

    South China University of Technology · Nanjing University · University of New South Wales +5

  27. PanoDP: Learning Collision-Free Navigation with Panoramic Depth and Differentiable Physics

    Mar 8, 2026Hao Zhong, Pei Chi, Jiang Zhao +4Panoramic Depth EstimationSafe Robot Navigation

    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. · Beihang University, Beijing, China. · The University of Queensland, Australia.

  28. Don't Freeze, Don't Crash: Extending the Safe Operating Range of Neural Navigation in Dense Crowds

    Mar 6, 2026Jiefu Zhang, Yang Xu, Vaneet AggarwalSafe Robot NavigationRobot Navigation

    Purdue University, USA

  29. Online Self-Training for Co-Adaptation in Hierarchical Diffusion Policies

    Mar 5, 2026Clemence Grislain, Mathilde Kappel, Olivier Sigaud +1Robot Policy LearningRobot Policy Adaptation

    ISIR, Sorbonne Université, CNRS, Paris, France

  30. VPWEM: Non-Markovian Visuomotor Policy with Working and Episodic Memory

    Mar 5, 2026Yuheng Lei, Zhixuan Liang, Hongyuan Zhang +1Robot Policy LearningVisuomotor Policy Learning

    School of Computing and Data Science, University of Hong Kong