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机器人

51 篇 · 资讯流
  2. 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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  4. 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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  5. arXiv cs.RO（机器人）

    JoyInside-VLM-Agent: Product-Conditioned Multimodal Policy Learning for Embodied Agents

    Embodied agents must translate multimodal observations and user requests into executable actions while adapting to produ

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  7. arXiv cs.RO（机器人）

    EmbodiedSmith: Scaling Embodied Data through Recursive Self-Improvement Flywheel in Simulation

    Scaling robotic foundation models requires diverse training data and reliable evaluation environments. Simulation offers

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  9. arXiv cs.RO（机器人）

    Visual Swarm Navigation via Deep Reinforcement Learning and Evolutionary Hybrid Design

    Swarm robotics presents a robust and cost-effective paradigm for advanced automation in complex, dynamic environments, s

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  10. arXiv cs.RO（机器人）

    Adaptive Mean Flow for Responsive Closed-Loop Robot Control

    Diffusion- and flow-based robot policies have recently become widespread in robotic Imitation Learning (IL) due to their

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  12. arXiv cs.RO（机器人）

    Managing Context and Communication in Distributed Agentic UAV Swarms

    Unmanned aerial vehicle (UAV) swarms increasingly rely on language-model agents to provide adaptive mission-level reason

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  14. arXiv cs.RO（机器人）

    GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives

    Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tin

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  15. arXiv cs.RO（机器人）

    GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed

    Autoregressive (AR) grounding models serialize spatial predictions, introducing sequential latency and imposing a causal

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  16. arXiv cs.RO（机器人）

    Text-to-3D Policy: Fine-Grained Language-Behavior Alignment for Unseen Specification Generalization

    3D visuomotor policies provide a strong foundation for spatially precise manipulation, yet current text-to-3D policies s

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