论文/arXiv 2610.23068·12 天前

自主空间机器人基础模型：架构、物理适应与验证

本文综述基础模型如何通过感知、预测、规划与动作支撑自主空间机器人，并在轨道操作和近距离操作验证路径中分析。

AI 整理

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• 端侧部署

原文链接：Foundation Models for Autonomous Space Robotics: Architectures, Physical Adaptation, and Validation（arXiv 2610.23068 · 发布日期：2026-10-16）

Foundation Models for Autonomous Space Robotics: Architectures, Physical Adaptation, and Validation

本文综述基础模型如何通过感知、预测、规划与动作支撑自主空间机器人，并在轨道操作和近距离操作验证路径中分析。

核心要点

• 空间机器人需在陌生动力学、困难感知和少人工干预下理解任务并行动。
• 综述沿感知、预测、规划、动作到部署验证梳理基础模型接口与预训练作用。
• 比较地面研究，指出向空间动力学和受限星载运行的迁移仍测试不足。
• 提出仿真到地面再到空间的迭代验证路径，并以卫星捕获串联接近、接触和恢复。

验证范围与局限：验证讨论聚焦轨道操作、近距离操作和卫星捕获示例，并强调空间迁移证据不足。

英文摘要 (Abstract)

Space robots must interpret tasks and act despite unfamiliar dynamics, difficult sensing conditions, and limited opportunities for human intervention. Foundation models offer reusable perceptual and behavioral knowledge, but their value depends on how that knowledge reaches physical execution. This critical review follows space-specific requirements through perception, prediction, planning, and action to deployment and validation, emphasizing orbital manipulation and proximity operations. Terrestrial comparisons establish benefits of particular pretraining stages and model interfaces; their transfer to space dynamics and constrained onboard operation remains insufficiently tested. Event cameras offer timely motion observations across strong illumination contrasts, while spiking neural networks provide possible routes to sparse local computation. We examine how sensor degradation, state estimation and computing choices affect feedback and recovery. Higher action throughput need not yield fresher feedback; lower processor power can also coexist with higher energy per inference. We organize validation as an iterative sim-to-ground-to-space pathway, connecting physical tests with telemetry-based diagnosis and closed-loop revalidation. A satellite-capture example links observations to approach, contact and recovery, while a corresponding protocol separates generalization from adaptation with limited target-domain interaction. These comparisons identify what models already contribute and the physical evidence needed to support autonomous space operation.

作者：Zizhe Wang, Jia Deng, Xin Lu, Zehao Jia, Yi Huang, Yao Zhu, Jianing Li

来源

本页事实对应的公开页面，以原文为准。

1. arXiv 2610.23068：Foundation Models for Autonomous Space Robotics: Architectures, Physical Adaptation, and Validation访问 2026-10-21