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机器人

66 篇 · 资讯流
  2. arXiv cs.RO（机器人）

    Unifying Embodied Foundation Models via a Model-to-Policy Formulation

    Vision-language-action (VLA) models and world-action models (WAMs) have emerged as promising approaches to robot learnin

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  3. arXiv cs.RO（机器人）

    Auditable and Deployable Multi-Agent Motion Planning via Posetal Games from Legal Guidelines

    When robots are deployed in the real-world, they must interact with other agents and accomplish their own goals while ad

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  5. arXiv cs.AI（人工智能）

    Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion

    Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors

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  7. arXiv cs.RO（机器人）

    Tactile-Guided Robot Learning: From Representation Learning to Foundation Models

    Tactile sensing is becoming central to robust, adaptive, and dexterous robotic manipulation. Beyond its traditional role

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  8. arXiv cs.AI（人工智能）

    ChunkAct: Action Chunking for Agentic Robotics

    Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, moti

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  9. arXiv cs.RO（机器人）

    Collaborative Planning for UAV-UGV Teams under Operational Constraints via Masked Error-bounded Neuro-Symbolic Diffusion

    Collaborative planning under operational constraints is essential for heterogeneous robot teams in large-scale missions.

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  10. arXiv cs.AI（人工智能）

    UniW(A)M: A Unified Mixture-of-Experts Framework for World and World-Action Models

    World models (WMs) and world-action models (WAMs) focus on future world prediction and executable action generation, res

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  12. arXiv cs.RO（机器人）

    Thinker-WM: A Unified World Model with Shared Multimodal Representations for Embodied Intelligence

    World models have emerged as a promising paradigm for embodied AI, yet existing systems often remain fragmented in the m

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  13. arXiv cs.RO（机器人）

    Let the Mind Conceive, Let the Hand Achieve: Following Multimodal Instructions for Long-Horizon Robotic Manipulation

    A robot following a multi-step instruction needs to act on the right objects in the right order, even as the scene chang

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  15. arXiv cs.RO（机器人）

    MARGoS: A Configuration-Driven Platform for Reproducible MARL Experiments in ARGoS

    Multi-agent reinforcement learning (MARL) has become a prominent research direction, particularly within collective robo

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