English(EN) VISION-SLS: Safe Perception-Based Control from Learned Visual Representations via System Level Synthesis

VISION-SLS 通过学习到的视觉抽象实现安全、可扩展的视觉运动控制

作者 PulseAugur 编辑部 · [2 个来源] · 2026-04-27 18:20

研究人员开发了 VISION-SLS，一种用于利用视觉输入的安全控制系统的创新方法。该方法为约束满足提供了强大的保证，即使在传感器噪声、部分可观测性和非线性动力学存在的情况下也是如此。该系统将学习到的低维观测图与通过系统级综合优化的因果输出反馈策略相结合，实现了实用且可扩展的视觉运动控制。 AI

影响通过视觉输入实现更安全、更高效的机器人系统控制，有可能提高在复杂环境中的性能。

排序理由详细介绍安全控制系统新方法的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · Antoine P. Leeman, Shuyu Zhan, Melanie N. Zeilinger, Glen Chou · 2026-04-29 04:00

VISION-SLS: 基于学习的视觉表示的安全感知控制通过系统级综合实现

arXiv:2604.24894v1 Announce Type: cross Abstract: We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction guarantees under calibrated uncertainty bounds despite partial observability, sens…
arXiv cs.CV TIER_1 English(EN) · Glen Chou · 2026-04-27 18:20

VISION-SLS：基于学习的视觉表示通过系统级综合实现安全的基于感知的控制

We propose VISION-SLS, a method for nonlinear output-feedback control from high-resolution RGB images which provides robust constraint satisfaction guarantees under calibrated uncertainty bounds despite partial observability, sensor noise, and nonlinear dynamics. To enable scalab…