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English(EN) Orbit-Planner: Towards Latent World Models for On-Orbit Obstacle Avoidance of Satellite Agents

新的Orbit-Planner模型增强了卫星的障碍物规避能力

研究人员开发了Orbit-Planner,这是一种新颖的两阶段潜在世界模型,专为卫星在轨导航和避障而设计。该模型学习动作条件下的航天器动力学,在潜在空间中预测未来状态,并使用物理探测器将这些潜在预测转换回物理状态。实验表明,Orbit-Planner在长时域潜在滚动中具有有效性,并在NVIDIA Isaac Sim的闭环避障模拟中实现了91.7%的成功率。 AI

影响 该模型可以提高在复杂轨道环境中自主卫星运行的安全性和效率。

排序理由 该集群描述了一篇关于用于卫星导航的新颖模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的Orbit-Planner模型增强了卫星的障碍物规避能力

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该集群描述了一篇关于用于卫星导航的新颖模型的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhijian Li, Chao Ren, Peijin Wang, Xian Sun ·

    Orbit-Planner:迈向用于卫星在轨避障的潜在世界模型

    arXiv:2608.16651v1 Announce Type: cross Abstract: Satellite agents for on-orbit navigation tasks need to predict collision risks using limited onboard observations. However, conventional planners often rely on predefined maps and fixed environmental assumptions, limiting their ad…