Sebastian Trimpe

収録論文 41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

• WarpMPC: Large-Batch MPC on GPU via ADMM with Unrolled $LDL^\top$ Factorization
  2026/7/1
• Generative AI for Safe and Photorealistic Drone Light Shows
  2026/6/1
• Learning to Race in Minutes: Infoprop Dyna on the Mini Wheelbot
  2026/5/1
• Preferential Bayesian Optimization with Crash Feedback
  2026/4/1
• How to Model Your Crazyflie Brushless
  2026/3/1
• The Mini Wheelbot Dataset: High-Fidelity Data for Robot Learning
  2026/1/1
• Fine-Tuning of Neural Network Approximate MPC without Retraining via Bayesian Optimization
  2025/12/1
• Newtonian and Lagrangian Neural Networks: A Comparison Towards Efficient Inverse Dynamics Identification
  2025/6/1
• Diffusion-Based Approximate MPC: Fast and Consistent Imitation of Multi-Modal Action Distributions
  2025/4/1
• The Mini Wheelbot: A Testbed for Learning-based Balancing, Flips, and Articulated Driving
  2025/2/1
• CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
  2025/1/1
• On Foundation Models for Dynamical Systems from Purely Synthetic Data
  2024/12/1
• Simulation-Aided Policy Tuning for Black-Box Robot Learning
  2024/11/1
• Learning deformable linear object dynamics from a single trajectory
  2024/7/1
• Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)
  2023/12/1
• Data-efficient Deep Reinforcement Learning for Vehicle Trajectory Control
  2023/11/1
• Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations
  2023/7/1
• Robust Direct Data-Driven Control for Probabilistic Systems
  2023/6/1
• Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test
  2023/3/1
• Learning Fast and Precise Pixel-to-Torque Control
  2022/8/1
• The Wheelbot: A Jumping Reaction Wheel Unicycle
  2022/7/1
• Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
  2022/2/1
• Safe Value Functions
  2021/5/1
• GoSafe: Globally Optimal Safe Robot Learning
  2021/5/1
• Structured learning of rigid-body dynamics: A survey and unified view from a robotics perspective
  2020/12/1
• Robot Learning with Crash Constraints
  2020/10/1
• Learning Event-triggered Control from Data through Joint Optimization
  2020/8/1
• Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures
  2020/5/1
• Learning Constrained Dynamics with Gauss Principle adhering Gaussian Processes
  2020/4/1
• Safe and Fast Tracking on a Robot Manipulator: Robust MPC and Neural Network Control
  2019/12/1
• Actively Learning Gaussian Process Dynamics
  2019/11/1
• Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization
  2019/10/1
• A Learnable Safety Measure
  2019/10/1
• Classified Regression for Bayesian Optimization: Robot Learning with Unknown Penalties
  2019/7/1
• Data-efficient Auto-tuning with Bayesian Optimization: An Industrial Control Study
  2018/12/1
• Gait learning for soft microrobots controlled by light fields
  2018/9/1
• Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization
  2017/3/1
• Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers
  2017/3/1
• Automatic LQR Tuning Based on Gaussian Process Global Optimization
  2016/5/1
• Depth-Based Object Tracking Using a Robust Gaussian Filter
  2016/2/1
• A New Perspective and Extension of the Gaussian Filter
  2015/4/1