Robotics

Papers

• State Representation Learning For Control: An Overview (2018)
  Timothée Lesort, Natalia Díaz-Rodríguez, Jean-François Goudou, et al.
  17.39
• Shared Autonomy Via Deep Reinforcement Learning (2018)
  Siddharth Reddy, Anca D. Dragan, Sergey Levine
  15.40
• Control Synthesis from Linear Temporal Logic Specifications using Model-Free Reinforcement Learning (2019)
  Alper Kamil Bozkurt et al.
  14.93
• SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning (2025)
  Haozhan Li et al.
  11.71
• Learning Representations In Model-free Hierarchical Reinforcement Learning (2018)
  Jacob Rafati, David C. Noelle
  11.49
• Barc: Backward Reachability Curriculum For Robotic Reinforcement Learning (2018)
  Boris Ivanovic, James Harrison, Apoorva Sharma, et al.
  10.74
• Flow Matching Policy Gradients (2025)
  David McAllister et al.
  10.62
• A Survey On Physics Informed Reinforcement Learning: Review And Open Problems (2023)
  Chayan Banerjee, Kien Nguyen, Clinton Fookes, et al.
  9.76
• RL-100: Performant Robotic Manipulation with Real-World Reinforcement Learning (2025)
  Kun Lei et al.
  9.46
• Application of Deep Reinforcement Learning to UAV Swarming for Ground Surveillance (2025)
  Ra\'ul Arranz et al.
  9.43
• Secure Planning Against Stealthy Attacks via Model-Free Reinforcement Learning (2020)
  Alper Kamil Bozkurt et al.
  9.41
• Drl4route: A Deep Reinforcement Learning Framework For Pick-up And Delivery Route Prediction (2023)
  Xiaowei Mao, Haomin Wen, Hengrui Zhang, et al.
  9.41
• Real-world Human-robot Collaborative Reinforcement Learning (2020)
  Ali Shafti, Jonas Tjomsland, William Dudley, et al.
  9.41
• To The Noise And Back: Diffusion For Shared Autonomy (2023)
  Takuma Yoneda, Luzhe Sun, Ge Yang, et al.
  8.82
• Rsoccer: A Framework For Studying Reinforcement Learning In Small And Very Small Size Robot Soccer (2021)
  Felipe B. Martins, Mateus G. MacHado, Hansenclever F. Bassani, et al.
  8.35
• SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling (2025)
  Yixian Zhang et al.
  8.03
• Model-Free Learning of Safe yet Effective Controllers (2021)
  Alper Kamil Bozkurt et al.
  7.50
• A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data (2024)
  Adrian Remonda et al.
  7.50
• Skill-critic: Refining Learned Skills For Hierarchical Reinforcement Learning (2023)
  Ce Hao, Catherine Weaver, Chen Tang, et al.
  7.50
• Dream to Drive with Predictive Individual World Model (2025)
  Yinfeng Gao and Qichao Zhang and Da-wei Ding and Dongbin Zhao
  7.29
• Dynamics-adaptive Continual Reinforcement Learning Via Progressive Contextualization (2022)
  Tiantian Zhang, Zichuan Lin, Yuxing Wang, et al.
  7.16
• What Matters for Batch Online Reinforcement Learning in Robotics? (2025)
  Perry Dong et al.
  6.80
• ACL-QL: Adaptive Conservative Level in Q-Learning for Offline Reinforcement Learning (2024)
  Kun Wu et al.
  6.52
• Continual Model-Based Reinforcement Learning with Hypernetworks (2020)
  Yizhou Huang et al.
  6.34
• Goal Recognition As Reinforcement Learning (2022)
  Leonardo Rosa Amado, Reuth Mirsky, Felipe Meneguzzi
  6.34
• DEAS: DEtached value learning with Action Sequence for Scalable Offline RL (2025)
  Changyeon Kim et al.
  6.04
• Optimizing Navigation And Chemical Application in Precision Agriculture With Deep Reinforcement Learning And Conditional Action Tree (2025)
  Mahsa Khosravi et al.
  5.96
• SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning (2024)
  Jianye Xu et al.
  5.84
• Learning To Forecast Aleatoric And Epistemic Uncertainties Over Long Horizon Trajectories (2023)
  Aastha Acharya, Rebecca Russell, Nisar R. Ahmed
  5.84
• Rl_reach: Reproducible Reinforcement Learning Experiments For Robotic Reaching Tasks (2021)
  Pierre Aumjaud, David McAuliffe, Francisco Javier Rodríguez Lera, et al.
  5.84
• Continuous Value Iteration (CVI) Reinforcement Learning And Imaginary Experience Replay (IER) For Learning Multi-goal, Continuous Action And State Space Controllers (2019)
  Andreas Gerken, Michael Spranger
  5.84
• Unsupervised Meta-Testing with Conditional Neural Processes for Hybrid Meta-Reinforcement Learning (2025)
  Suzan Ece Ada and Emre Ugur
  5.82
• Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarm (2025)
  Hyeonjun Kim et al.
  5.65
• Learning to Ball: Composing Policies for Long-Horizon Basketball Moves (2025)
  Pei Xu et al.
  5.63
• World Model for AI Autonomous Navigation in Mechanical Thrombectomy (2025)
  Harry Robertshaw et al.
  5.63
• Safe Multi-Agent Navigation guided by Goal-Conditioned Safe Reinforcement Learning (2025)
  Meng Feng et al.
  5.59
• Towards Generalizable Safety in Crowd Navigation via Conformal Uncertainty Handling (2025)
  Jianpeng Yao et al.
  5.57
• Hybrid Action Based Reinforcement Learning for Multi-Objective Compatible Autonomous Driving (2025)
  Guizhe Jin et al.
  5.54
• Dual Advantage Fields (2026)
  Alexey Zemtsov et al.
  5.49
• Composing Dextrous Grasping and In-hand Manipulation via Scoring with a Reinforcement Learning Critic (2025)
  Lennart R\"ostel et al.
  5.40
• Human-in-the-loop Online Rejection Sampling for Robotic Manipulation (2025)
  Guanxing Lu et al.
  5.26
• Learning Curriculum Policies For Reinforcement Learning (2018)
  Sanmit Narvekar, Peter Stone
  5.24
• First Order Model-Based RL through Decoupled Backpropagation (2025)
  Joseph Amigo et al.
  5.21
• Multi-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous Driving (2025)
  Guizhe Jin et al.
  5.04
• roto 2.0: The Robot Tactile Olympiad (2026)
  Elle Miller et al.
  4.94
• Evolutionary Policy Optimization (2025)
  Jianren Wang and Yifan Su and Abhinav Gupta and Deepak Pathak
  4.87
• TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance (2025)
  Yuyang Liu et al.
  4.69
• Beyond Policy Optimization: A Data Curation Flywheel for Sparse-Reward Long-Horizon Planning (2025)
  Yutong Wang et al.
  4.64
• Mining the Long Tail: A Comparative Study of Data-Centric Criticality Metrics for Robust Offline Reinforcement Learning in Autonomous Motion Planning (2025)
  Antonio Guillen-Perez
  4.64
• Reinforcement Learning For Online Testing Of Autonomous Driving Systems: A Replication And Extension Study (2024)
  Luca Giamattei, Matteo Biagiola, Roberto Pietrantuono, et al.
  4.52