Kei Ota

The University of Tokyo

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

• マルチモーダルロボットデモにおける指示と軌道の不一致の監査
  データ監査2026/8/8

  ロボットのデモデータセットに含まれる、軌道は正しいが指示が誤っているデータを検出・修正する監査手法を提案した。

• Auditing Instruction-Trajectory Mismatches in Multimodal Robot Demonstrations
  2026/8/1
• See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs
  2026/6/1
• YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale
  2026/6/1
• Continuous Reasoning for Vision-Language-Action
  2026/6/1
• See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs
  2026/6/1
• Continuous Reasoning for Vision-Language-Action
  2026/5/29
• Touch2Insert: Zero-Shot Peg Insertion by Touching Intersections of Peg and Hole
  2026/3/1
• Simultaneous Extrinsic Contact and In-Hand Pose Estimation via Distributed Tactile Sensing
  2025/12/1
• Analytic Conditions for Differentiable Collision Detection in Trajectory Optimization
  2025/9/1
• AIRoA MoMa Dataset: A Large-Scale Hierarchical Dataset for Mobile Manipulation
  2025/9/1
• Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations
  2025/8/1
• Modality Selection and Skill Segmentation via Cross-Modality Attention
  2025/4/1
• Zero-Shot Peg Insertion: Identifying Mating Holes and Estimating SE(2) Poses with Vision-Language Models
  2025/3/1
• Autonomous Robotic Assembly: From Part Singulation to Precise Assembly
  2024/6/1
• Robust In-Hand Manipulation with Extrinsic Contacts
  2024/3/1
• Tactile Estimation of Extrinsic Contact Patch for Stable Placement
  2023/9/1
• Tactile-Filter: Interactive Tactile Perception for Part Mating
  2023/3/1
• H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactions
  2022/10/1
• Object Memory Transformer for Object Goal Navigation
  2022/3/1
• OPIRL: Sample Efficient Off-Policy Inverse Reinforcement Learning via Distribution Matching
  2021/9/1
• Training Larger Networks for Deep Reinforcement Learning
  2021/2/1
• Deep Reactive Planning in Dynamic Environments
  2020/11/1
• Data-Efficient Learning for Complex and Real-Time Physical Problem Solving using Augmented Simulation
  2020/11/1
• Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?
  2020/3/1
• Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path
  2020/3/1
• Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning
  2019/3/1