Robotic RL

RL: Reinforcement Learning

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28 papers in the last four weeks, up 180% on the four weeks before. 0.3% of all new papers.

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DexSim2Real: Foundation Model-Guided Sim-to-Real Transfer for Generalizable Dexterous Manipulation
May 3, 2026Zijian Zeng, Fei Ding, Huiming Yang +2Domain Randomization Dexterous Manipulation
Tsinghua University · Alibaba Group · Bengbu University +1
Towards Efficient and Expressive Offline RL via Flow-Anchored Noise-conditioned Q-Learning
May 3, 2026Sungyoung Lee, Dohyeong Kim, Eshan Balachandar +2Distributional RL Q-Learning
The University of Texas at Austin, Austin, TX, USA · Independent Researcher, Seoul, South Korea.
Learning to Race in Minutes: Infoprop Dyna on the Mini Wheelbot
May 1, 2026Devdutt Subhasish, Henrik Hose, Sebastian TrimpeRobot Skill Learning Autonomous Racing
Institute for Data Science in Mechanical Engineering, RWTH Aachen University, 52062 Aachen
E $^2$ DT: Efficient and Effective Decision Transformer with Experience-Aware Sampling for Robotic Manipulation
Apr 30, 2026Kaiyan Zhao, Borong Zhang, Yiming Wang +4Long-Horizon Robotic Manipulation Transformer
School of Computer Science, Wuhan University, Wuhan 430072, China · State Key Lab of Internet of Things for Smart City and Department of Computer Information Science, University of Macau, Macao 999078, China
RHyVE: Competence-Aware Verification and Phase-Aware Deployment for LLM-Generated Reward Hypotheses
Apr 30, 2026Feiyu Wu, Xu Zheng, Zhuocheng Wang +2Reinforcement Learning LLM-Guided RL
School of Cyber Engineering, Xidian University
Can Tabular Foundation Models Guide Exploration in Robot Policy Learning?
Apr 30, 2026Buqing Ou, Frederike DümbgenTabular Foundation Models Robot Policy Learning
Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA · Inria, Département d’informatique de l’ENS, CNRS, PSL Research University, Paris, France
TSN-Affinity: Similarity-Driven Parameter Reuse for Continual Offline Reinforcement Learning
Apr 28, 2026Dominik Żurek, Kamil Faber, Marcin Pietron +2Continual Learning Robotic RL
AGH University of Krakow, Poland · American University, Washington, DC, USA
Distributional Reinforcement Learning via the Cramér Distance
Apr 26, 2026Vanya Aziz, Ivo Nowak, E. M. T HendrixDistributional RL Robotic RL
HAW Hamburg · de Málaga
Benefits of Low-Cost Bio-Inspiration in the Age of Overparametrization
Apr 22, 2026Kevin Godin-Dubois, Anil Yaman, Anna V. KononovaRobotic Control Robotic RL
Vrije Universiteit Amsterdam, Netherlands · LIACS, Leiden Universiteit, Netherlands
Learning Hybrid-Control Policies for High-Precision In-Contact Manipulation Under Uncertainty
Apr 21, 2026Hunter L. Brown, Geoffrey Hollinger, Stefan LeeRobotic Control Contact-Rich Robotic Manipulation
Collaborative Robotics and Intelligent Systems Institute, Oregon State University, Corvallis, OR
Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients?
Apr 20, 2026Ku Onoda, Paavo Parmas, Manato Yaguchi +1Policy Gradient Robotic RL
The University of Tokyo, Tokyo, Japan
Fuzzy Logic Theory-based Adaptive Reward Shaping for Robust Reinforcement Learning (FARS)
Apr 17, 2026Hürkan Şahin, Van Huyen Dang, Erdi Sayar +2Reward Shaping Robotic RL
Automatic Control Group (RAT), Paderborn University, 33098 Paderborn, Germany
Abstract Sim2Real through Approximate Information States
Apr 16, 2026Yunfu Deng, Yuhao Li, Josiah P. HannaSim-to-Real Transfer State Abstraction
Department of Computer Sciences, University of Wisconsin–Madison, Madison, WI 53706 USA · Manning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA 01003 USA
Generalizable Dense Reward for Long-Horizon Robotic Tasks
Mar 31, 2026Silong Yong, Stephen Sheng, Carl Qi +6Reinforcement Learning Long-Horizon Robotic Manipulation
Carnegie Mellon University · Amazon Robotics · UT Austin
Large Reward Models: Generalizable Online Robot Reward Generation with Vision-Language Models
Mar 17, 2026Yanru Wu, Weiduo Yuan, Esteban Martinez Licon +4Long-Horizon Robotic Manipulation Robot Skill Learning
USC Physical Superintelligence Lab
ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors
Mar 16, 2026Zifan Xu, Ran Gong, Maria Vittoria Minniti +10Long-Horizon Robotic Manipulation Robot Skill Learning
Robotics and AI Institute · University of Texas at Austin · Sony AI
Learning to Build: Autonomous Robotic Assembly of Stable Structures Without Predefined Plans
Feb 27, 2026Jingwen Wang, Johannes Kirschner, Paul Rolland +2Robotic Construction Sequential Decision Making
Lab of Creative Computation, ´Ecole Polytechnique F´ed´erale de Lausanne · Swiss Data Science Center
Learning Human-Like Badminton Skills for Humanoid Robots
Feb 9, 2026Yeke Chen, Shihao Dong, Xiaoyu Ji +12Humanoid Robot Control Robotic RL
Adaptive Robotic Controls Lab (ArcLab), Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China · EngineAI Robotics Technology Co., Ltd., Shenzhen, China
Scalable Dexterous Robot Learning with AR-based Remote Human-Robot Interactions
Feb 7, 2026Yicheng Yang, Ruijiao Li, Lifeng Wang +7Reinforcement Learning Robotic RL
UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations
Dec 12, 2025Tingyu Yuan, Biaoliang Guan, Wen Ye +8Cross-Embodiment Robot Learning Robotic RL
CASIA · UCAS · XJTU +3
A Primer on SO(3) Action Representations in Deep Reinforcement Learning
Oct 13, 2025Martin Schuck, Sherif Samy, Angela P. SchoelligRobotic RL RL Exploration
Technical University of Munich · University of Girona
What Matters in RL-Based Methods for Object-Goal Navigation? An Empirical Study and A Unified Framework
Oct 2, 2025Hongze Wang, Boyang Sun, Jiaxu Xing +5Robotic RL Robotic Perception
Computer Vision and Geometry Group, ETH Zurich, Switzerland · Robotics and Perception Group, University of Zurich, Switzerland · Robotic Systems Lab, ETH Zurich, Switzerland +2
HARL-A: An Extensible Benchmark Framework for Heterogeneous Multi-Agent Adversarial Reinforcement Learning in IsaacLab
Sep 26, 2025Isaac Peterson, Christopher Allred, Jacob Morrey +1RL Benchmarks Robotic RL
Utah State University · US DEVCOM Army Research Laboratory
Robot Drummer: Learning Rhythmic Skills for Humanoid Drumming
Jul 15, 2025Asad Ali Shahid, Francesco Braghin, Loris RovedaLong-Horizon Robotic Manipulation Robot Skill Learning
IDSIA, SUPSI, Lugano, Switzerland · Department of Mechanical Engineering, Politecnico di Milano, Italy
Adaptive Reinforcement Learning for Unobservable Random Delays
Jun 17, 2025John Wikman, Alexandre Proutiere, David BromanReinforcement Learning Robotic RL
EECS and Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden.
Shared Modular Recurrence in Contextual MDPs for Universal Morphology Control
Jun 10, 2025Laurens Engwegen, Max Weltevrede, Caroline Horsch +2Robotic Control Reinforcement Learning
Delft University of Technology Delft, The Netherlands
HERB: Human-augmented Efficient Reinforcement learning for Bin-packing
Apr 23, 2025Gojko Perovic, Nuno Ferreira Duarte, Atabak Dehban +3Robotic RL Robotics
BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy, and with the Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy. · Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal.
CONTHER: Context-Aware Reinforcement Learning for Robotic Manipulation with Sparse Rewards
Mar 20, 2025Maria Makarova, Qian Liu, Dzmitry TsetserukouReinforcement Learning Experience Replay
Intelligent Space Robotics Laboratory, Center for Digital Engineering, Skolkovo Institute of Science and Technology (Skoltech), 121205 Moscow, Russia · Department of Computer Science and Technology, Dalian University of Technology, China
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
Mar 19, 2025Kevin Wang, Ishaan Javali, Michał Bortkiewicz +2Reinforcement Learning Robotic RL
Princeton University · Warsaw University of Technology · Warsaw University of Technology, Tooploox, IDEAS Research Institute
Passivity-Centric Safe Reinforcement Learning for Contact-Rich Robotic Tasks
Mar 1, 2025Heng Zhang, Gokhan Solak, Sebastian Hjorth +1Robotic Control Contact-Rich Robotic Manipulation
HRI2 Lab, Istituto Italiano di Tecnologia, Genoa, Italy · Ph.D. program of national interest in Robotics and Intelligent Machines (DRIM) and University of Genova, Genoa, Italy

May 3, 2026, cs.ROJ/K move · Enter open · S save

DexSim2Real: Foundation Model-Guided Sim-to-Real Transfer for Generalizable Dexterous Manipulation

Zijian Zeng, Fei Ding, Huiming Yang, Xianwei Li+1

Tsinghua University · Alibaba Group · Bengbu University+1

Domain Randomization Dexterous Manipulation Sim-to-Real Transfer Generalization in Robotic Manipulation Robotic RL VLMs for Robotics

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Sim-to-real transfer remains a critical bottleneck for deploying dexterous manipulation policies learned in simulation to real-world robots. Existing approaches rely on manually designed domain randomization or task-specific adaptation, limiting their generalizability across diverse manipulation scenarios. We present DexSim2Real, an integrated framework that leverages vision-language foundation models to bridge the sim-to-real gap for dexterous manipulation. Our system combines three components: (1) Foundation Model-Guided Domain Randomization (FM-DR), which uses a vision-language model as a visual realism critic to optimize simulation parameters via closed-loop CMA-ES, complementing text-based approaches like DrEureka with direct visual feedback; (2) a Tactile-Visual Cross-Attention Policy (TVCAP) that adapts cross-attention visuo-tactile fusion to zero-shot sim-to-real RL; and (3) a Progressive Skill Curriculum (PSC) that builds on LLM-based task decomposition with a difficulty scheduler tailored to contact-rich dexterous tasks. Extensive experiments on six challenging manipulation tasks with blinded evaluation demonstrate that DexSim2Real achieves a 78.2% average real-world success rate, outperforming DrEureka and DeXtreme while reducing the sim-to-real performance gap to only 8.3%.

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Latest papers 184