# 基于信念行动，需要时观察：用于间歇感知下导航的贝叶斯空间世界模型

> 原文链接：https://robotics.hellobike.com/papers/2026-10-08-2610-11591
> 频道：papers | 更新日期：2026-10-08 | 标签：arxiv, cs.RO
> 核心摘要：针对共享传感器间歇感知下的导航，ALONE以贝叶斯空间信念按需观测，并在仿真场景和真实室内飞行中验证。

# 基于信念行动，需要时观察：用于间歇感知下导航的贝叶斯空间世界模型

::: v-pre
> 原文链接：[Acting from Belief, Looking When Needed: A Bayesian Spatial World Model for Navigation under Intermittent Perception](https://arxiv.org/abs/2610.11591)（arXiv 2610.11591 · 发布日期：2026-10-08）

**Acting from Belief, Looking When Needed: A Bayesian Spatial World Model for Navigation under Intermittent Perception**

针对共享传感器间歇感知下的导航，ALONE以贝叶斯空间信念按需观测，并在仿真场景和真实室内飞行中验证。

## 核心要点

- 研究共享传感器被其他任务占用时，导航观测中断造成的间歇感知问题。
- ALONE用动作传播结构化空间信念，并用选择性观测和几何先验校正。
- 模型将信念解码为空间估计，并预测可靠性图以决定是否请求新观测。
- 仿真闭环成功率达98%和97%，成功试验中需新深度观测的决策步很少。

**验证范围与局限**：验证限于两类仿真场景的无人机导航和10次真实室内飞行深度观测实验。

## 英文摘要 (Abstract)

Robot navigation commonly uses wide-coverage, high-frequency sensing to reduce partial observability; this reliance becomes restrictive when another task temporarily redirects a shared sensor from navigation, interrupting navigation-relevant observations. We study navigation under intermittent perception: acting from an internal spatial belief and looking again only when execution needs a new observation, potentially freeing the shared sensor for other tasks between navigation observations. ALONE, a Bayesian spatial world model, propagates a structured spatial belief using executed actions and corrects it with selectively acquired observations; learned priors over common geometric structures infer unobserved structure from available observation history. It decodes the belief into a spatial estimate for the motion-planning module and predicts a reliability map expressing confidence in the estimate's accuracy. ALONE requests an observation only if insufficient reliability hinders navigation and new evidence should make relevant-region spatial information more reliable; otherwise, it continues acting from the propagated belief. We instantiate ALONE for drone navigation with intermittent single-camera depth images. Across two simulated scene families, it achieves 98% and 97% closed-loop success at a 10 Hz decision rate. Among successful trials, median fractions of decision steps requiring a new depth observation are only 0.9% and 1.3%, respectively, demonstrating high navigation success with substantially reduced observation demand. Real-world indoor flight experiments further validate navigation under intermittent depth observations, with all 10 trials successful.

作者：Feihong Yang, Xiang Long, Jincheng Yu, Jianfei Zhang, Guangjun Ge, Chao Wang, Yu Wang
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## 原始参考来源 (Sources)

- [arXiv 2610.11591：Acting from Belief, Looking When Needed: A Bayesian Spatial World Model for Navigation under Intermittent Perception](https://arxiv.org/abs/2610.11591)