# 超越可见范围的感知：面向机器人自主的不完备性感知场景理解

> 原文链接：https://robotics.hellobike.com/papers/2026-10-13-2610-18670
> 频道：papers | 更新日期：2026-10-13 | 标签：arxiv, cs.RO
> 核心摘要：提出面向机器人自主的不完备性感知场景理解愿景，围绕三类不完备性组织方法并展望信念中心4D表示。

# 超越可见范围的感知：面向机器人自主的不完备性感知场景理解

::: v-pre
> 原文链接：[Perception Beyond the Visible: Incompleteness-Aware Scene Understanding for Robot Autonomy](https://arxiv.org/abs/2610.18670)（arXiv 2610.18670 · 发布日期：2026-10-13）

**Perception Beyond the Visible: Incompleteness-Aware Scene Understanding for Robot Autonomy**

提出面向机器人自主的不完备性感知场景理解愿景，围绕三类不完备性组织方法并展望信念中心4D表示。

## 核心要点

- 动机是机器人需从部分且有噪观测推理，现有系统在遮挡、新物体和传感退化下假设失效。
- 方法围绕证据、知识和传感可靠性三类不完备性，讨论相应的场景理解挑战。
- 已讨论的研究贡献包括amodal perception、semantic occupancy forecasting、开放世界理解、标签高效学习和不确定性引导多模态融合。
- 未来方向是信念中心4D场景表示，并结合主动感知与安全适应来通过交互降低不确定性。

## 英文摘要 (Abstract)

Reliable robot autonomy requires reasoning about the world from partial and noisy observations. However, many perception systems model only visible scene regions, rely on fixed semantic categories, and assume reliable sensor measurements. These assumptions break under occlusion, novel object encounters, and sensor degradation. In this paper, I present a research vision for incompleteness-aware scene understanding. I organize this vision around three fundamental challenges: incomplete evidence, incomplete knowledge, and incomplete sensor reliability. I discuss my research contributions toward addressing these challenges through amodal perception, semantic occupancy forecasting, open-world scene understanding, label-efficient learning, and uncertainty-guided multi-modal fusion. Building on these contributions, I outline future research directions toward belief-centric 4D scene representations. These representations aim to jointly model geometry, semantics, motion, and uncertainty. I also discuss active sensing and safe adaptation strategies that allow robots to reduce uncertainty through interaction. The goal is to develop calibrated and actionable scene representations that support reliable autonomy in dynamic, open-world environments.

作者：Rohit Mohan
:::

## 原始参考来源 (Sources)

- [arXiv 2610.18670：Perception Beyond the Visible: Incompleteness-Aware Scene Understanding for Robot Autonomy](https://arxiv.org/abs/2610.18670)