Sicun Gao

収録論文 27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

• Sensitivity Shaping for Latent Modeling
  2026/6/1
• Learning Quadruped Walking from Seconds of Demonstration
  2026/3/7
• RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning
  2026/1/1
• Learning to Nudge: A Scalable Barrier Function Framework for Safe Robot Interaction in Dense Clutter
  2026/1/1
• Sequence Modeling for Time-Optimal Quadrotor Trajectory Optimization with Sampling-based Robustness Analysis
  2025/6/1
• Improving Value Estimation Critically Enhances Vanilla Policy Gradient
  2025/5/1
• Safe Human Robot Navigation in Warehouse Scenario
  2025/3/1
• Estimating Control Barriers from Offline Data
  2025/3/1
• Controllable Motion Generation via Diffusion Modal Coupling
  2025/3/1
• SEEV: Synthesis with Efficient Exact Verification for ReLU Neural Barrier Functions
  2024/10/1
• Hamilton-Jacobi Reachability in Reinforcement Learning: A Survey
  2024/7/1
• Mollification Effects of Policy Gradient Methods
  2024/5/1
• Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller
  2024/4/1
• Extremum-Seeking Action Selection for Accelerating Policy Optimization
  2024/4/1
• Iterative Reachability Estimation for Safe Reinforcement Learning
  2023/9/1
• Sequential Neural Barriers for Scalable Dynamic Obstacle Avoidance
  2023/7/1
• Patching Approximately Safe Value Functions Leveraging Local Hamilton-Jacobi Reachability Analysis
  2023/4/1
• Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models
  2023/3/1
• Accelerating Multi-Agent Planning Using Graph Transformers with Bounded Suboptimality
  2023/1/1
• Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
  2022/10/1
• Learning Control Admissibility Models with Graph Neural Networks for Multi-Agent Navigation
  2022/10/1
• Learning-based Motion Planning in Dynamic Environments Using GNNs and Temporal Encoding
  2022/10/1
• Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions
  2022/7/1
• Safe Control with Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction methods
  2022/2/1
• Safe Nonlinear Control Using Robust Neural Lyapunov-Barrier Functions
  2021/9/1
• Stabilizing Neural Control Using Self-Learned Almost Lyapunov Critics
  2021/7/1
• Neural Lyapunov Control
  2020/5/1