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机器人

51 篇 · 资讯流
  2. arXiv cs.RO（机器人）

    Explore, Execute, Evolve: A Skill Acquisition and Reuse Loop for Embodied Agents

    Vision-language-action and world-action models have demonstrated impressive capabilities in robotics, yet generalization

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  3. arXiv cs.RO（机器人）

    DROM: A Language-Guided Diffusion Framework for Multi-Skill Robotic Manipulation

    Learning robust manipulation policies for diverse, long-horizon tasks from limited demonstrations remains a fundamental

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  5. arXiv cs.RO（机器人）

    Rethinking Causal Action Tokenization with Conditional Annealing in Flow Matching

    Autoregressive Vision-Language-Action (VLA) models offer a scalable path to robot learning, yet existing action tokenize

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  6. arXiv cs.RO（机器人）

    Memory in the Sky: Low-Altitude Question Answering with Multi-Agent Memory Aggregation

    This paper studies low-altitude question answering (LAQA), in which distributed unmanned aerial vehicle (UAV) memories a

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  7. arXiv cs.RO（机器人）

    From Pixel to Poses: Object-centric Tool Manipulation Learning from Human Demonstrations

    Scaling up robotic manipulation is primarily bottlenecked by the scarcity of real-world robot data. While recent approac

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  8. arXiv cs.RO（机器人）

    JRDB-AVR: An Active Visual Reasoning Benchmark for Embodied Agents in Real-World Environments

    In complex embodied visual reasoning scenarios, an agent often has only a limited field of view, and the evidence needed

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  10. arXiv cs.RO（机器人）

    Watch, Recall, Act: Always-On Robots in Concurrent Embodied Streams

    An always-on robot faces an endless stream that never resets: instructions arrive and lapse, the scene changes, and its

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  11. arXiv cs.RO（机器人）

    PointCast: One World Model for Rigid, Articulated, and Deformable Object Manipulation

    World models are useful for robotic manipulation because robots can predict how actions change the states of objects bef

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  13. arXiv cs.RO（机器人）

    MATE: Multi-Agent Virtual Teleoperation Platform for Humanoid Collaboration Data Collection

    Humanoid robots require diverse embodied experiences to acquire complex loco-manipulation and collaborative skills. Howe

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  14. arXiv cs.RO（机器人）

    Hierarchical Floorplan-Guided Vision-Language Exploration for Embodied Question Answering

    Embodied Question Answering (EQA) requires an agent to explore a previously unseen environment, gather relevant informat

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