Chao Yu

収録論文 44本 ・ フィジカルAI/ロボット学習

※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。

論文

• AgilePE: 自己対戦強化学習による自律UAV追跡・回避
  強化学習/UAV2026/8/14

  自己対戦強化学習を用いて、UAVの追跡・回避行動をエンドツーエンドで学習し、シミュレーションから実機へのゼロショット転送を実現したシステムを提案する。

• LAMP: Latent Motion Prior-Guided Real-World Learning for Dexterous Hand Manipulation
  2026/7/1
• Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents
  2026/7/1
• UMI-Bench 1.0: An Open and Reproducible Real-World Benchmark for Tabletop Robotic Manipulation with UMI Data
  2026/6/1
• STEAM: Self-Supervised Temporal Ensemble Advantage Modeling for Real-World Robot Learning
  2026/6/1
• LaWAM: Latent World Action Models for Efficient Dynamics-Aware Robot Policies
  2026/6/1
• VISTA: Vision-Grounded and Physics-Validated Adaptation of UMI data for VLA Training
  2026/6/1
• HALO:Closing Sim-to-Real Gap for Heavy-loaded Humanoid Agile Motion Skills via Differentiable Simulation
  2026/3/1
• StreamingVLA: Streaming Vision-Language-Action Model with Action Flow Matching and Adaptive Early Observation
  2026/3/1
• Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models
  2026/2/1
• RLinf-USER: A Unified and Extensible System for Real-World Online Policy Learning in Embodied AI
  2026/2/1
• WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL
  2026/2/1
• RoboScape-R: Unified Reward-Observation World Models for Generalizable Robotics Training via RL
  2025/12/1
• $π_\texttt{RL}$: Online RL Fine-tuning for Flow-based Vision-Language-Action Models
  2025/10/29
• RLinf-VLA: A Unified and Efficient Framework for Reinforcement Learning of Vision-Language-Action Models
  2025/10/1
• JuggleRL: Mastering Ball Juggling with a Quadrotor via Deep Reinforcement Learning
  2025/9/1
• World4RL: Diffusion World Models for Policy Refinement with Reinforcement Learning for Robotic Manipulation
  2025/9/1
• SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
  2025/9/1
• D3P: Dynamic Denoising Diffusion Policy via Reinforcement Learning
  2025/8/1
• Spec-VLA: Speculative Decoding for Vision-Language-Action Models with Relaxed Acceptance
  2025/7/30
• ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning
  2025/5/28
• What Can RL Bring to VLA Generalization? An Empirical Study
  2025/5/26
• ReinFlow: Fine-tuning Flow Matching Policy with Online Reinforcement Learning
  2025/5/1
• Toward Real-World Cooperative and Competitive Soccer with Quadrupedal Robot Teams
  2025/5/1
• Hysteresis-Aware Neural Network Modeling and Whole-Body Reinforcement Learning Control of Soft Robots
  2025/4/1
• Multi-Robot System for Cooperative Exploration in Unknown Environments: A Survey
  2025/3/1
• VolleyBots: A Testbed for Multi-Drone Volleyball Game Combining Motion Control and Strategic Play
  2025/2/1
• Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
  2025/2/1
• What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Study
  2024/12/1
• Neural Internal Model Control: Learning a Robust Control Policy via Predictive Error Feedback
  2024/11/1
• Multi-UAV Formation Control with Static and Dynamic Obstacle Avoidance via Reinforcement Learning
  2024/10/1
• Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning
  2024/9/1
• Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation
  2024/9/1
• FlightBench: Benchmarking Learning-based Methods for Ego-vision-based Quadrotors Navigation
  2024/6/1
• Long-horizon Locomotion and Manipulation on a Quadrupedal Robot with Large Language Models
  2024/4/1
• MASP: Scalable GNN-based Planning for Multi-Agent Navigation
  2023/12/1
• Active Neural Topological Mapping for Multi-Agent Exploration
  2023/11/1
• OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control
  2023/9/1
• LAGOON: Language-Guided Motion Control
  2023/6/1
• Safe Offline Reinforcement Learning with Real-Time Budget Constraints
  2023/6/1
• Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation
  2023/2/1
• Asynchronous Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-Robot Cooperative Exploration
  2023/1/1
• Multi-Agent Vulnerability Discovery for Autonomous Driving with Hazard Arbitration Reward
  2021/12/1
• DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments
  2018/9/1