Robust RL

RL: Reinforcement Learning

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Reinforcement Learning on Cost-Constrained Quadrupedal Hardware
Jul 29, 2026Javier C. Weddington, Bence P. Ölveczky, Stephen A. BaccusDynamical Systems Reinforcement Learning
Neurosciences Interdepartmental Program, Stanford University, Stanford, CA 94305 USA · Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138 USA · Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305 USA
Reinforcement Learning for Code Optimization
Jul 28, 2026Pierre Chambon, Kunhao Zheng, Juliette Decugis +2RL for Code Generation Reinforcement Learning
FAIR at Meta · Inria · Université Paris Dauphine
Towards Robust Reinforcement Learning for Small-Scale Language Model Agents
Jul 27, 2026Md Rezwanul Haque, Md. Milon Islam, Fakhri KarrayRL for Language Models LLM Alignment
Centre for Pattern Analysis and Machine Intelligence, Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Ontario, Canada · Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh · Department of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates
Evaluating Fuzz Testing for Reinforcement Learning Agents
Jul 27, 2026Zhibin Kang, Hanmo You, Dong Wang +2Safe RL Robust RL
College of Intelligence and Computing, Tianjin University, Tianjin, China
WARL: Wrench-Augmented Reinforcement Learning for Task-Agnostic Learning in Legged Robots
Jul 27, 2026Keita Yoneda, Kento Kawaharazuka, Kei OkadaCurriculum RL RL Exploration
Department of Mechano-Informatics, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan. · AI Center, Graduate School of Information Science and Technology, The University of Tokyo, Japan.
Robust Asynchronous Q-Learning under Reward and State Corruption via Batching
Jul 23, 2026Sreejeet Maity, Aritra MitraAsynchronous RL Q-Learning
Department of Electrical and Computer Engineering, North Carolina State University.
HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems
Jul 21, 2026Nicolò Botteghi, Gabriele Pascali, Urban Fasel +1RL Control Hypernetworks
MOX, Department of Mathematics · Politecnico di Milano · Milano, Italy +3
The Mechanism Matters: When Knowledge Graphs Help Reinforcement Learning
Jul 21, 2026Mohammed Sameer SyedRobust RL
Rethinking the Suitability of Reinforcement Learning Algorithms Under Practical Transfer Constraints
Jul 19, 2026Hany Hamed, Abhishek Naik, Colin Bellinger +1Domain Randomization Reinforcement Learning
University of Alberta · 3Alberta Machine Intelligence Institute (Amii) · 7Generative Bionics +4
Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids
Jul 17, 2026Josef Hoppe, Sarra Bouchkati, Farah Nasr +7Partially Observable RL Robust RL
Computational Network Science, RWTH Aachen University · IAEW, RWTH Aachen University · E.ON impulse GmbH +2
SMC-ES: Automated synthesis of formally verified control policies
Jul 16, 2026Riccardo Curcio, Toni Mancini, Enrico TronciFormal Verification Safe RL
Department of Computer Science, Sapienza University of Rome, via Salaria 113, 00198 Rome, Italy
Learning Robust Execution in Robotic Manipulation with Agentic Reinforcement Learning
Jul 15, 2026Xiaopeng Zhang, Yueyang Weng, Qi Liu +2Agentic RL Robot Failure Recovery
School of Inteligence Science and Engineering, the Harbin Institute of Technology Shenzhen, 518055, China. · Faculty of Robot Science and Engineering, Northeastern University, Shenyang, 110819, China.
Robust In-Hand Manipulation via Priors in Reinforcement Learning and Mechanical Design
Jul 13, 2026Yifei Chen, Shihan Lu, Ed Colgate +1Robotic Hand Design Robotic Grasping
Center for Robotics and Biosystems, Northwestern University
Gimitest: A Comprehensive Tool for Testing Reinforcement Learning Policies
Jul 8, 2026Dennis Gross, Quentin Mazouni, Helge Spieker +1Robust RL
Simula Research Laboratory, Oslo, Norway
ADP: Adversarial Dynamics Priors for Physically Grounded Humanoid Locomotion
Jul 3, 2026Seokju Lee, Jeongtae Lee, Jeonghyeok Lim +6Adversarial Training Humanoid Robot Locomotion
Mechatronics, Systems and Control Lab (MSC Lab), Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Yuseong-gu, Daejeon 34141, Republic of Korea · Samsung Electronics, Future Robotics AI Group, Seoul, Republic of Korea · School of Electrical Engineering, Hanyang University, Ansan 15588, Republic of Korea +1
Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning
Jul 3, 2026Jialun Cao, Fernando Acero, David Šiška +1Robust Markov Decision Processes Maximum Entropy RL
School of Mathematics, University of Edinburgh, United Kingdom. · J.P. Morgan AI Research, United Kingdom. · Department of Mathematics, Imperial College London, United Kingdom.
Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL
Jul 1, 2026Jongchan Park, Seungjun Oh, Seungho Baek +1Reinforcement Learning Robot Policy Generalization
Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea · Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, Republic of Korea
Deep Reinforcement Learning for Spacecraft Attitude Control During Atmospheric Re-Entry
Jun 30, 2026Alexander Fabisch, Melvin Laux, Mariela De Lucas Álvarez +2RL Control Feedback Control
Robotics Innovation Center, German Research Center for Artificial Intelligence (DFKI GmbH), Germany · 2Airbus Defence and Space GmbH, Germany
RoAd-RL: A Unified Library and Benchmark for Robust Adversarial Reinforcement Learning
Jun 29, 2026Adithya Mohan, Daniel Kriegl, Torsten SchönRL Benchmarks Reinforcement Learning
AImotion Bavaria · Technische Hochschule Ingolstadt · Ingolstadt, Germany
Continual Robot Policy Learning via Variational Neural Dynamics
Jun 25, 2026Jiaxu Xing, Zhiyuan Zhu, Yunfan Ren +4Robot Policy Learning Robot Policy Adaptation
Robotics and Perception Group, University of Zurich
ROAD-VLA: Robust Online Adaptation via Self-Distillation for Vision-Language-Action Models
Jun 24, 2026Kejing Wang, Toan Nguyen, Minh Hoang Nguyen +2Robot Policy Adaptation VLM Adaptation
Applied Artificial Intelligence Initiative Deakin University Geelong, Australia · Air Force Research Laboratory USA
Adversarial observations in probabilistic State-Space Models for robust Reinforcement Learning
Jun 18, 2026M. Santos-Pascual, D. Ríos InsuaAdversarial Attacks Partially Observable RL
1Inst. Math. Sciences, Spanish Nat. Research Council, Madrid, Spain · Universidad Autónoma de Madrid, Escuela de Doctorado, Madrid, Spain
Steering Generative Reinforcement Learning into Stable Robotic Controller
Jun 15, 2026Yixuan Wang, Shutong Ding, Ke Hu +3Latent Action Learning Robotic RL
1ShanghaiTech University
Incentives and Evidence in Learned Service Orchestration
Jun 15, 2026Syed Izhan Khilji, Alireza Furutanpey, Schahram DustdarRL Control Reinforcement Learning
†Distributed Systems Group (DSG), TU Wien, Vienna, Austria · ‡Coovally.ai, Barcelona, Spain
ADAPT: Analytical Disturbance-Aware Policy Training for Humanoid Locomotion
Jun 15, 2026Bofan Lyu, Jindou Jia, Kuangji Zuo +7Robotic Control Humanoid Robot Locomotion
1MARS Lab, Nanyang Technological University
Distribution-Agnostic Robust Trajectory Optimization via Chance-Constrained Reinforcement Learning
Jun 11, 2026Yashdeep Chaudhary, Roberto Armellin, Harry Holt +1Trajectory Optimization Constrained RL
Faculty of Engineering, Waipapa Taumata Rau – University of Auckland, 20 Symonds Street, Auckland, 1010, New Zealand · Advanced Concepts Team, European Space Research and Technology Centre, ESA, Noordwijk, 2201 AZ, The Netherlands · Department of Industrial Engineering, Alma Mater Studiorum - Università di Bologna, Via Zamboni 33, Bologna, 40126, Italy
PolicyGuard: Towards Test-time and Step-level Adversary (Backdoor) Defense for Reinforcement Learning Agent
Jun 11, 2026Junfeng Guo Heng HuangBackdoor Attacks Backdoor Defense
Computer Science, University of Maryland College Park, USA.
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
ReflectiChain: Epistemic Grounding in LLM-Driven World Models for Supply Chain Resilience
Jun 9, 2026Jia LuoConstrained RL LLM-Guided RL
School of Foreign Languages, Huazhong University of Science and Technology, Wuhan 430074, China.
Scaling by Diversified Experience for Vision-Language-Action Models
Jun 8, 2026Leiyu Wang, Zhaofengnian Wang, Xueqi Li +3VLM Robustness Vision-Language-Action Models
Shanghai Jiao Tong University · Shanghai Innovation Institute · Tongji University +3

Jul 29, 2026, cs.ROJ/K move · Enter open · S save

Reinforcement Learning on Cost-Constrained Quadrupedal Hardware

Javier C. Weddington, Bence P. Ölveczky, Stephen A. Baccus

Neurosciences Interdepartmental Program, Stanford University, Stanford, CA 94305 USA · Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138 USA · Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305 USA

Dynamical Systems Reinforcement Learning Partially Observable RL Sim-to-Real Transfer RL for Legged Locomotion Robust RL

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Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the sim-to-real gap. The chasm of simulation to deployment in hardware lies in the delay of the actuator reaching the commanded position. On platforms such as the Mini Pupper 2, a measured >50 ms transport delay transforms the locomotion task from a standard Markov decision process into a partially observable one. In this paper, we take a biologically inspired approach of handling noisy and delayed feedback to close the sim-to-real gap, thereby expanding the capability of reinforcement learning on cost-constrained hardware. Using a low-cost quadrupedal hardware platform, we find that using a forward model of the average actuator delay, paired with a time-aware neural network results in robust locomotion. Additionally, our time-aware neural network learned a central pattern generator (CPG): a self-sustaining rhythmic gait that is robust to +320 ms latency perturbations, mirroring the CPGs found in the spinal cords of vertebrates. We posit that temporal self-organization may be a general strategy for cost-constrained locomotion.

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