David Hoeller

収録論文 17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

• Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
  2025/11/1
• RSL-RL: A Learning Library for Robotics Research
  2025/9/1
• Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning
  2025/6/1
• Learning Agile Locomotion on Risky Terrains
  2023/11/1
• ANYmal Parkour: Learning Agile Navigation for Quadrupedal Robots
  2023/6/1
• Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments
  2023/1/1
• Advanced Skills by Learning Locomotion and Local Navigation End-to-End
  2022/9/1
• Neural Scene Representation for Locomotion on Structured Terrain
  2022/6/1
• Locomotion Policy Guided Traversability Learning using Volumetric Representations of Complex Environments
  2022/3/1
• Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning
  2021/9/1
• Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning
  2021/8/1
• Learning a State Representation and Navigation in Cluttered and Dynamic Environments
  2021/3/1
• Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation
  2021/3/1
• Joint Space Control via Deep Reinforcement Learning
  2020/11/1
• Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion
  2020/9/1
• Practical Reinforcement Learning For MPC: Learning from sparse objectives in under an hour on a real robot
  2020/3/1
• Deep Value Model Predictive Control
  2019/10/1