RL for Robotics

RL: Reinforcement Learning

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31 papers in the last four weeks, up 675% on the four weeks before. 0.3% of all new papers.

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Latest papers 155

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Improving Robotic Generalist Policies via Flow Reversal Steering
Jun 11, 2026Andy Tang, William Chen, Andrew Wagenmaker +2RL for Robotics Robot Policy Learning
Stanford University · UC Berkeley
Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer
Jun 11, 2026Aryan Naveen, Haitong Ma, Haldun Balim +1RL for Robotics Reinforcement Learning
Massachusetts Institute of Technology · Harvard School of Engineering and Applied Sciences
Stubborn: A Streamlined and Unified Reinforcement Learning Framework for Robust Motion Tracking and Fall Recovery for Humanoids
Jun 11, 2026Xiao Ren, Yuhui Yang, Zongbiao Weng +2RL for Robotics Reinforcement Learning
Southern University of Science and Technology, Shenzhen 518055, China
TacCoRL: Integrating Tactile Feedback into VLA via Simulation
Jun 10, 2026Siyu Ma, Yuqi Liang, Chang Yu +5RL for Robotics Robot Skill Learning
University of California, Los Angeles · University of California, San Diego · 4Peking University +1
AllDayNav: Lifelong Navigation via Real-World Reinforcement Learning
Jun 9, 2026Hang Yin, Yinan Liang, Jiazhao Zhang +4RL for Robotics Continual Robot Learning
Tsinghua University, Beijing 100084, China · Galbot Robotics, Beijing, China · Peking University, Beijing 100871, China +1
Embodiment-conditioned Generalist Control for Multirotor Aerial Robots
Jun 9, 2026Orestis Konstantaropoulos, Welf Rehberg, Mihir Kulkarni +1RL for Robotics Aerial Robotics
Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
SARM2: Multi-Task Stage Aware Reward Modeling for Self Improving Robotic Manipulation
Jun 9, 2026Qianzhong Chen, Hau Zheng, Justin Yu +8RL for Robotics Reward Modeling
Stanford University · UC Berkeley · Shanghai Jiao Tong University
TORL-VLA: Tactile Guided Online Reinforcement Learning for Contact-Rich Manipulation
Jun 8, 2026Huaihang Zheng, Yi Yang, Kai Ma +8RL for Robotics Long-Horizon Robotic Manipulation
Meituan · State Key Lab of Multimodal Artificial Intelligence Systems, Institute of Automation, CAS · Beijing Institute of Technology +2
Disturbance-Aware Aerial Robotics for Ethical Wildlife Monitoring
Jun 6, 2026Mahmut Osmanovic, Isac Paulsson, Teddy LazebnikRL for Robotics Aerial Robotics
Department of Computing, Jonkoping University, Jonkoping, Sweden · Department of Information Systems, University of Haifa, Haifa, Israel
Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations
Jun 6, 2026Xinglong Zhang, Cong Li, Hangjie Mo +13Robotic Control RL for Robotics
College of Intelligence Science and Technology, National University of Defense Technology, Deya Road, Changsha, 410003, Hunan, China. · School of Management, Hefei University of Technology, Nanyihuan Road, Hefei, 230002,2026 Anhui, China. · State Key NanjingLaboratoryUniversityfor Novel(SuzhouSoftwareCampus),TechnologyTaihuandRoad,the Suzhou,School of215163,ScienceChina.and Technology, 4School of Computation, Information and Technology, Technical University of Munich, Boltzmann Strasse, Munich, 85748, Germany. +5
LadderMan: Learning Humanoid Perceptive Ladder Climbing
Jun 4, 2026Siheng Zhao, Yuanhang Zhang, Ziqi Lu +6RL for Robotics Humanoid Robot Locomotion
Amazon FAR · USC · UC Berkeley +2
M3imic: Learning a Versatile Whole-Body Controller for Multimodal Motion Mimicking
Jun 3, 2026Zuxing Lu, Ziang Zheng, Yao Lyu +7RL for Robotics Humanoid Robot Control
School of Automation, Southeast University, Nanjing 210096, China · School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China · Department of Robotics, Mohamed Bin Zayed University of Artificial Intelligence, Abu Dhabi 7909, UAE
Inverse Manipulation through Symbolic Planning and Residual Operator Learning
Jun 3, 2026Yigit Yildirim, Giuseppe Rauso, Riccardo Caccavale +1RL for Robotics Robot Skill Learning
CREATE Consortium, Italy · Department of Electrical Engineering and Information Technologies, Universit`a di Napoli Federico II, Italy
AgenticRL: Self-Refining Agentic Reinforcement Learning for Vision-Conditioned UAV Navigation
Jun 2, 2026Roohan Ahmed Khan, Yasheerah Yaqoot, Amir Atef Habel +2RL for Robotics Agentic RL
PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion
Jun 2, 2026Zihong Lu, Zongzhuo Liu, Huaxu Li +5RL for Robotics Aerial Robotics
1SUSTech · 2HITSZ · 3PCL +1
AirDreamer: Generalist Drone Navigation with World Models
Jun 2, 2026Zian Liu, Andong Yang, Chunkai Yang +3RL for Robotics World Models for Robotics
Institute for AI Industry Research, Tsinghua University, Beijing, China. · Department of Electronic Engineering, Tsinghua University, Beijing, China. · School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China.
Reinforcement Learning from Cross-domain Videos with Video Prediction Model
Jun 2, 2026Zhao Yang, Xinrui Zu, Jacob E. Kooi +5RL for Robotics Imitation Learning
VU Amsterdam, The Netherlands · ISAE-SUPAERO, France
HOIST: Humanoid Optimization with Imitation and Sample-efficient Tuning for Manipulating Suspended Loads
May 29, 2026Songyang Liu, Shunyu Yao, Dingyuan Huang +1RL for Robotics Humanoid Robot Control
Department of Civil and Coastal Engineering University of Florida United States
RDGen: Demonstration Generation for High-Quality Robot Learning via Reinforcement Learning
May 29, 2026Zijian Zhu, Menglin Zou, Zhuang Li +2RL for Robotics Robot Skill Learning
LLM-Guided Future Hypotheses for Horizon-Aware Exploration in Multi-Step Robot Manipulation
May 28, 2026Mohammad Khoshnazar, Andrew Melnik, Michael BeetzRL for Robotics Reinforcement Learning
Institute of Artificial Intelligence, University of Bremen, Germany.
Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation
May 27, 2026Jiahe Pan, Stelian Coros, Jitendra Malik +1RL for Robotics Tactile Sensing
1ETH Zürich · 2UC Berkeley
Learning, locomotion, and navigation of soft synthetic snakes in three-dimensional, heterogeneous environments
May 24, 2026Xiaotian Zhang, Ali Albazroun, Tixian Wang +3RL for Robotics Robotics Simulation
Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana–Champaign · Department of Mechanical and Aerospace Engineering, Hong Kong University of Science and Technology · Department of Mechanical Science and Engineering, University of Illinois Urbana–Champaign
Vision-Guided Outdoor Flight and Obstacle Evasion via Reinforcement Learning
May 23, 2026Shiladitya Dutta, Aayush Gupta, Varun Saran +1RL for Robotics UAV Navigation
College of Engineering, Department of Electrical Engineering and Computer Science, University of California Berkeley
Robotic Strawberry Harvesting with Robust Vision and Deep Reinforcement Learning based Sim-to-Real Control
May 22, 2026Al Bashir, Shao-Yang Chang, Partho Ghose +3RL for Robotics Instance Segmentation
Department of Biological & Agricultural Engineering, Texas A&M University, College Station, TX 77843, USA · Department of Biomechatronics Engineering, National Taiwan University, 10617, Taipei City, Taiwan · Texas A&M AgriLife Research, Texas A&M University System, Dallas, TX 75252, USA
From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
May 22, 2026Christian Gumbsch, Leonardo Barcellona, Lennard Schünemann +7RL for Robotics Multimodal Reward Modeling
University of Amsterdam · 2Catholic University of Leuven · 3Toyota Research Institute +1
Vision-Based Agile Landing on Turbulent Waters
May 22, 2026Dimosthenis Angelis, Leonard Bauersfeld, Davide Scaramuzza +1RL for Robotics Aerial Robotics
Department of Electrical and Photonics Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark · Robotics and Perception Group, Department of Informatics, University of Zurich, Zurich, Switzerland
SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-based Humanoid Control
May 21, 2026Jingyan Zhang, Han Liang, Ruichi Zhang +6RL for Robotics Humanoid Robot Control
ShanghaiTech University, China · Bytedance Seed, China · University of Pennsylvania, USA +2
roto 2.0: The Robot Tactile Olympiad
May 20, 2026Elle Miller, Jayaram Reddy, Ayush Deshmukh +4RL for Robotics Dexterous Manipulation
University of Edinburgh, UK · National University Singapore, Singapore
CaMeRL: Collision-Aware and Memory-Enhanced Reinforcement Learning for UAV Navigation in Multi-Scale Obstacle Environments
May 14, 2026Hong Hong, Feiyu Liao, Yongheng Liang +3RL for Robotics Reinforcement Learning
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China, and the Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou, China
Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation
May 12, 2026Hao Wang, Joshua Bowden, Colton Crosby +1RL for Robotics Reinforcement Learning
University of Southern California · Stanford University

Jun 11, 2026, cs.ROJ/K move · Enter open · S save

Improving Robotic Generalist Policies via Flow Reversal Steering

Andy Tang, William Chen, Andrew Wagenmaker, Chelsea Finn+1

Stanford University · UC Berkeley

RL for Robotics Robot Policy Learning Robot Skill Learning Generalization in Robotic Manipulation Robotic Manipulation Activation Steering

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Generalist policies can learn a wide range of skills from diverse robot datasets. In order to solve or improve on challenging new tasks, we need a way to infer and invoke the appropriate actions from the policy's rich behavioral prior, especially when directly commanding the policy fails. We focus on flow matching generalists and propose Flow Reversal Steering (FRS): a method that takes suboptimal but ``reasonable'' actions, finds their latent noises by passing them through the flow policy in reverse, and maps them to nearby generalist action modes. We evaluate FRS across many simulated and real-world manipulation settings. First, FRS can turn coarse semantic guidance from humans or vision-language models (VLMs) into corresponding good robot actions, improving zero-shot control. These gains can be distilled with behavioral cloning by training an auxiliary policy to output noises that the generalist maps to good actions -- showing up to 95% absolute task success rate boosts in under a minute of training. Finally, FRS enables policy improvement by bootstrapping reinforcement learning with semantic knowledge, improving on several tasks that standard RL fails to improve on.

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Latest papers 155