Maria Bauza

収録論文 23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

• Exploiting Policy Idling for Dexterous Manipulation
  2025/8/1
• ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
  2025/6/1
• Gemini Robotics: Bringing AI into the Physical World
  2025/3/1
• DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots
  2024/9/1
• Learning to Learn Faster from Human Feedback with Language Model Predictive Control
  2024/2/1
• simPLE: a visuotactile method learned in simulation to precisely pick, localize, regrasp, and place objects
  2023/7/1
• RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
  2023/6/1
• FingerSLAM: Closed-loop Unknown Object Localization and Reconstruction from Visuo-tactile Feedback
  2023/3/1
• Tac2Pose: Tactile Object Pose Estimation from the First Touch
  2022/4/1
• Tactile Object Pose Estimation from the First Touch with Geometric Contact Rendering
  2020/12/1
• Tactile SLAM: Real-time inference of shape and pose from planar pushing
  2020/11/1
• Experience-Embedded Visual Foresight
  2019/11/1
• Accurate Vision-based Manipulation through Contact Reasoning
  2019/11/1
• Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video
  2019/10/1
• Tactile Mapping and Localization from High-Resolution Tactile Imprints
  2019/4/1
• Combining Physical Simulators and Object-Based Networks for Control
  2019/4/1
• Augmenting Physical Simulators with Stochastic Neural Networks: Case Study of Planar Pushing and Bouncing
  2018/8/1
• A Data-Efficient Approach to Precise and Controlled Pushing
  2018/7/1
• Tactile Regrasp: Grasp Adjustments via Simulated Tactile Transformations
  2018/3/1
• Robotic Pick-and-Place of Novel Objects in Clutter with Multi-Affordance Grasping and Cross-Domain Image Matching
  2017/10/1
• GP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs
  2017/9/1
• A probabilistic data-driven model for planar pushing
  2017/4/1
• More than a Million Ways to Be Pushed: A High-Fidelity Experimental Dataset of Planar Pushing
  2016/4/1