Dinesh Jayaraman

収録論文 49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

• LENS: LLM-guided Environment Simplification for Planning and Control in Clutter
  2026/7/1
• Expanding Spatial and Temporal Context for Robotic Imitation Learning With Scene Graphs
  2026/6/1
• OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies
  2026/3/9
• TiPToP: A Modular Open-Vocabulary Robot Manipulation System That Plans
  2026/3/1
• OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies
  2026/3/1
• Tether: Autonomous Functional Play with Correspondence-Driven Trajectory Warping
  2026/3/1
• Real-World Reinforcement Learning of Active Perception Behaviors
  2025/12/1
• Maestro: Orchestrating Robotics Modules with Vision-Language Models for Zero-Shot Generalist Robots
  2025/11/1
• TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance
  2025/9/1
• RICL: Adding In-Context Adaptability to Pre-Trained Vision-Language-Action Models
  2025/8/1
• VLMgineer: Vision Language Models as Robotic Toolsmiths
  2025/7/1
• RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies
  2025/6/1
• Leveling the Playing Field: Carefully Comparing Classical and Learned Controllers for Quadrotor Trajectory Tracking
  2025/6/1
• ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos
  2025/3/1
• Vision Language Models are In-Context Value Learners
  2024/11/1
• Task-Oriented Hierarchical Object Decomposition for Visuomotor Control
  2024/11/1
• Eurekaverse: Environment Curriculum Generation via Large Language Models
  2024/11/1
• Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems
  2024/9/1
• DrEureka: Language Model Guided Sim-To-Real Transfer
  2024/6/1
• Privileged Sensing Scaffolds Reinforcement Learning
  2024/5/1
• Recasting Generic Pretrained Vision Transformers As Object-Centric Scene Encoders For Manipulation Policies
  2024/5/1
• Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models
  2024/4/1
• Can Transformers Capture Spatial Relations between Objects?
  2024/3/1
• DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
  2024/3/1
• Memory-Consistent Neural Networks for Imitation Learning
  2023/10/1
• Eureka: Human-Level Reward Design via Coding Large Language Models
  2023/10/1
• Universal Visual Decomposer: Long-Horizon Manipulation Made Easy
  2023/10/1
• Open X-Embodiment: Robotic Learning Datasets and RT-X Models
  2023/10/1
• LIV: Language-Image Representations and Rewards for Robotic Control
  2023/6/1
• Planning Goals for Exploration
  2023/3/1
• Dynamic Grasping with a Learned Meta-Controller
  2023/2/1
• Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning
  2022/12/1
• VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
  2022/10/1
• Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport
  2022/10/1
• Vision-based Perimeter Defense via Multiview Pose Estimation
  2022/9/1
• Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming
  2022/6/1
• Know Thyself: Transferable Visual Control Policies Through Robot-Awareness
  2021/7/1
• Keyframe-Focused Visual Imitation Learning
  2021/6/1
• How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
  2021/4/1
• Model-Based Inverse Reinforcement Learning from Visual Demonstrations
  2020/10/1
• Fighting Copycat Agents in Behavioral Cloning from Observation Histories
  2020/10/1
• Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
  2020/6/1
• DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation
  2020/5/1
• Morphology-Agnostic Visual Robotic Control
  2019/12/1
• Emergence of Exploratory Look-Around Behaviors through Active Observation Completion
  2019/6/1
• REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning
  2019/5/1
• Manipulation by Feel: Touch-Based Control with Deep Predictive Models
  2019/3/1
• More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch
  2018/5/1
• Look-ahead before you leap: end-to-end active recognition by forecasting the effect of motion
  2016/5/1