RL for Robotics

RL: Reinforcement Learning

Ask about this topic

Overview

Reinforcement learning for robotics studies how robots can learn actions that achieve goals while coping with contact, uncertainty, and changing environments. Common methods include PPO, SAC, and TD3, often trained in parallel simulation with domain randomization; imitation learning, motion priors, and pretrained vision-language-action models increasingly provide useful starting points. Work spans humanoid locomotion, aerial and mobile navigation, and manipulation that uses tactile feedback, with safety filters and learned world models helping address risky or partially observed tasks. A central challenge is making learning more sample-efficient while ensuring that simulated skills and learned rewards remain reliable on real robots and unfamiliar situations.

Latest papers

CardsList

253 papers45 papers in the last four weeks, up 45% on the four weeks before. 0.3% of all new papers.

  1. OGPO: Sample Efficient Full-Finetuning of Generative Control Policies

    May 4, 2026Sarvesh Patil, Mitsuhiko Nakamoto, Manan Agarwal +14RL for RoboticsRL for Generative Models

    Carnegie Mellon University · University of California, Berkeley · University of Washington +1

  2. Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters

    May 4, 2026Lingxiao Kong, Cong Yang, Oya Deniz Beyan +1RL for RoboticsReinforcement Learning

    Fraunhofer Institute for Applied Information Technology FIT, Germany · Soochow University, China · University of Cologne, Germany +1

  3. Do We Really Need Immediate Resets? Rethinking Collision Handling for Efficient Robot Navigation

    May 4, 2026Shanze Wang, Xinming Zhang, Siwei Cheng +4RL for RoboticsRobot Navigation

    College of Information Science and Technology, Eastern Institute of Technology, Ningbo, China · Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong · School of Computer Science and Technology, University of Science and Technology of China, Hefei, China +2

  4. LaST-R1: Reinforcing Robotic Manipulation via Adaptive Physical Latent Reasoning

    Apr 30, 2026Hao Chen, Jiaming Liu, Zhonghao Yan +10RL for RoboticsRobot Foundation Models

    1The Chinese University of Hong Kong · 2State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · 3Simplexity Robotics

  5. Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies

    Apr 29, 2026Pokuang Zhou, Yuhao Zhou, Quan Khanh Luu +7Legged RoboticsRL for Robotics

    Purdue University, West Lafayette, IN, USA. · Istituto Italiano di Tecnologia, Genoa, Italy. · Columbia University, New York, NY, USA.

  6. Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance

    Apr 28, 2026Carson Kohlbrenner, Niraj Pudasaini, William Xie +3RL for RoboticsRobotic Tactile Sensing

    University of Colorado Boulder, 1111 Engineering Drive, Boulder, CO USA.

  7. RL Token: Bootstrapping Online RL with Vision-Language-Action Models

    Apr 24, 2026Charles Xu, Jost Tobias Springenberg, Michael Equi +4RL Fine-TuningVision-Language-Action Models

    Physical Intelligence

  8. Navigating the Clutter: Waypoint-Based Bi-Level Planning for Multi-Robot Systems

    Apr 22, 2026Jiabao Ji, Yongchao Chen, Yang Zhang +4RL for RoboticsMulti-Robot Motion Planning

    UC Santa Barbara · Massachusetts Institute of Technology · Harvard University +2

  9. Visual-Tactile Peg-in-Hole Assembly Learning from Peg-out-of-Hole Disassembly

    Apr 22, 2026Yongqiang Zhao, Xuyang Zhang, Zhuo Chen +3RL for RoboticsContact-Rich Robotic Manipulation

    Department of Engineering, King’s College London, Strand, London, WC2R 2LS, United Kingdom · Department of Informatics, King’s College London, Strand, London, WC2R 2LS, United Kingdom

  10. Vision-Language-Action Jump-Starting for Reinforcement Learning Robotic Agents

    Apr 15, 2026Angelo Moroncelli, Roberto Zanetti, Marco Maccarini +1RL for RoboticsData-Efficient Robot Learning

    University of Applied Science and Arts of Southern Switzerland, Department of Innovative Technologies, IDSIA-SUPSI, Lugano, Switzerland · Università della Svizzera Italiana, Faculty of Informatics, Lugano, Switzerland · Politecnico di Milano, Mechanical Department, Milano, Italy

  11. FastGrasp: Learning-based Whole-Body Control Method for Fast Dexterous Grasping with Mobile Manipulators

    Apr 14, 2026Heng Tao, Yiming Zhong, Zemin Yang +1RL for RoboticsRobotic Grasping

    ShanghaiTech University

  12. A hierarchical spatial-aware algorithm with efficient reinforcement learning for human-robot task planning and allocation in production

    Apr 14, 2026Jintao Xue, Xiao Li, Nianmin ZhangRobot Task PlanningHuman-Robot Collaboration

    Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR

  13. Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation

    Apr 12, 2026Fanxing Li, Shengyang Wang, Yuxiang Huang +5Quadrotor ControlVision-Based Robot Control

    Shanghai Jiao Tong University · Kunshan Duke University

  14. Precise Aggressive Aerial Maneuvers with Sensorimotor Policies

    Apr 7, 2026Tianyue Wu, Guangtong Xu, Zihan Wang +6UAV NavigationQuadrotor Control

    Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou, China. · Huzhou Institute of Zhejiang University, Huzhou, China. · Differential Robotics Technology Co., Ltd., Hangzhou, China.

  15. Biologically Inspired Event-Based Perception and Sample-Efficient Learning for High-Speed Table Tennis Robots

    Apr 6, 2026Ziqi Wang, Jingyue Zhao, Xun Xiao +5Robotic Table TennisRobotics

    National University of Defence Technology, Changsha 410073, Hunan, P.R.China · Defense Innovation Institute, AMS · Qiyuan Lab

  16. Learning from Imperfect Demonstrations via Temporal Behavior Tree-Guided Trajectory Repair

    Apr 5, 2026Aniruddh G. Puranic, Sebastian Schirmer, John S. Baras +1Robot Imitation LearningRL for Robotics

    Institute of Systems Research (ISR), University of Maryland, College Park, United States · DLR German Aerospace Center, Department of Unmanned Aircraft, Braunschweig, Germany

  17. Learning Dexterous Grasping from Sparse Taxonomy Guidance

    Apr 5, 2026Juhan Park, Taerim Yoon, Seungmin Kim +10RL for RoboticsRobotic Grasping

    Department of Artificial Intelligence, Korea University, Seoul, Korea · Korea University of Technology and Education, Cheonan, Korea · Naver AI Lab, Korea +4

  18. FSUNav: A Cerebrum-Cerebellum Architecture for Fast, Safe, and Universal Zero-Shot Goal-Oriented Navigation

    Apr 3, 2026Mingao Tan, Yiyang Li, Shanze Wang +2Open-Vocabulary Object NavigationRobot Navigation

    School of Computer Science, Shanghai Jiao Tong University, Shanghai, P. R. China · College of Information Science and Technology, Eastern Institute of Technology, Ningbo, P. R. China

  19. Bridging Discrete Planning and Continuous Execution for Redundant Robot

    Apr 2, 2026Teng Yan, Yue Yu, Yihan Liu +1Robot Motion PlanningMotion Planning

    Thrust of Artificial Intelligence, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China

  20. BAT: Balancing Agility and Stability via Online Policy Switching for Long-Horizon Whole-Body Humanoid Control

    Apr 1, 2026Donghoon Baek, Sang-Hun Kim, Sehoon HaRL for RoboticsHumanoid Robot Control

    Georgia Institute of Technology, Atlanta, GA, 30308, USA · Samsung Research

  21. Hybrid Framework for Robotic Manipulation: Integrating Reinforcement Learning and Large Language Models

    Mar 31, 2026Md Saad, Sajjad Hussain, Mohd SuhaibRobotic ManipulationLanguage-Conditioned Robot Manipulation

    Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India · School of Architecture, Technology and Engineering, University of Brighton, Brighton, UK

  22. SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning

    Mar 30, 2026Philip Schroeder, Thomas Weng, Karl Schmeckpeper +3RL for RoboticsMultimodal Reward Modeling

    MIT · RAI Institute

  23. Flip Stunts on Bicycle Robots using Iterative Motion Imitation

    Mar 30, 2026Jeonghwan Kim, Shamel Fahmi, Seungeun Rho +2Robot Imitation LearningImitation Learning

    RAI Institute, Cambridge, MA, USA · Georgia Institute of Technology, Atlanta, GA, USA

  24. Massive Parallel Deep Reinforcement Learning for Active SLAM

    Mar 26, 2026Martín Arce Llobera, Julio A. Placed, Mariano De Paula +1RL for RoboticsSimultaneous Localization and Mapping

    Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Autonoma de Buenos Aires, C1428EGA, Argentina · Instituto Tecnológico de Aragón (ITA) and the University of Zaragoza, María de Luna 3-7, Zaragoza, Spain

  25. QuadFM: Foundational Text-Driven Quadruped Motion Dataset for Generation and Control

    Mar 25, 2026Li Gao, Fuzhi Yang, Jianhui Chen +4Robot Motion GenerationLegged Robotics

    AMAP, Alibaba Group

  26. Cross-Modal Reinforcement Learning for Navigation with Degraded Depth Measurements

    Mar 23, 2026Omkar Sawant, Luca Zanatta, Grzegorz Malczyk +1Robot NavigationCross-Modal Learning

    Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Norway

  27. AGILE: A Comprehensive Workflow for Humanoid Loco-Manipulation Learning

    Mar 20, 2026Huihua Zhao, Rafael Cathomen, Lionel Gulich +6RL for RoboticsHumanoid Robot Control

  28. WINFlowNets: Warm-up Integrated Networks Training of Generative Flow Networks for Robotics and Machine Fault Adaptation

    Mar 18, 2026Zahin Sufiyan, Shadan Golestan, Yoshihiro Mitsuka +2Generative Flow NetworksRL for Robotics

    University of Alberta · Alberta Machine Intelligence Institute (Amii) · Mitsubishi Electric Corporation

  29. Efficient and Reliable Teleoperation through Real-to-Sim-to-Real Shared Autonomy

    Mar 17, 2026Shuo Sha, Yixuan Wang, Binghao Huang +2Robot TeleoperationShared Autonomy

    Columbia University · University of Pennsylvania

  30. NavThinker: Action-Conditioned World Models for Coupled Prediction and Planning in Social Navigation

    Mar 16, 2026Tianshuai Hu, Zeying Gong, Lingdong Kong +7Social Robot NavigationWorld Models for Robotics

    The Hong Kong University of Science and Technology · The Hong Kong University of Science and Technology (Guangzhou) · National University of Singapore +1