Arunkumar Byravan

収録論文 25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

• Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer
  2025/10/1
• Splatting Physical Scenes: End-to-End Real-to-Sim from Imperfect Robot Data
  2025/6/1
• Gemini Robotics: Bringing AI into the Physical World
  2025/3/1
• Proc4Gem: Foundation models for physical agency through procedural generation
  2025/3/1
• Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
  2025/2/1
• Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning
  2024/7/1
• Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning
  2024/5/1
• Real-World Fluid Directed Rigid Body Control via Deep Reinforcement Learning
  2024/2/1
• Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities
  2023/12/1
• Equivariant Data Augmentation for Generalization in Offline Reinforcement Learning
  2023/9/1
• Towards A Unified Agent with Foundation Models
  2023/7/1
• A Generalist Dynamics Model for Control
  2023/5/1
• Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning
  2023/4/1
• Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains
  2023/2/1
• NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields
  2022/10/1
• Evaluating model-based planning and planner amortization for continuous control
  2021/10/1
• Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes
  2021/10/1
• Learning Dynamics Models for Model Predictive Agents
  2021/9/1
• On Multi-objective Policy Optimization as a Tool for Reinforcement Learning: Case Studies in Offline RL and Finetuning
  2021/6/1
• Representation Matters: Improving Perception and Exploration for Robotics
  2020/11/1
• Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
  2019/10/1
• Motion-Nets: 6D Tracking of Unknown Objects in Unseen Environments using RGB
  2019/10/1
• Prospection: Interpretable Plans From Language By Predicting the Future
  2019/3/1
• SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control
  2017/10/1
• SE3-Nets: Learning Rigid Body Motion using Deep Neural Networks
  2016/6/1