# 线特征增强的 cuVSLAM：低纹理环境中的鲁棒视觉里程计

> 原文链接：https://robotics.hellobike.com/papers/2026-10-14-2610-20958
> 频道：papers | 更新日期：2026-10-14 | 标签：arxiv, cs.RO
> 核心摘要：面向低纹理环境中点特征视觉里程计失效问题，在线特征增强 cuVSLAM 中融入直线约束，并在 RGB-D 序列上验证精度提升。

# 线特征增强的 cuVSLAM：低纹理环境中的鲁棒视觉里程计

::: v-pre
> 原文链接：[Line-Augmented cuVSLAM: Robust Visual Odometry in Low-Texture Environments](https://arxiv.org/abs/2610.20958)（arXiv 2610.20958 · 发布日期：2026-10-14）

**Line-Augmented cuVSLAM: Robust Visual Odometry in Low-Texture Environments**

面向低纹理环境中点特征视觉里程计失效问题，在线特征增强 cuVSLAM 中融入直线约束，并在 RGB-D 序列上验证精度提升。

## 核心要点

- 仓库和生产设施常见无纹理、重复或反光场景，但含稳定直线边缘。
- 以 Plücker 坐标和 4-DOF 正交表示建模线，并加入鲁棒点到线残差。
- 线状态参与逐帧高斯牛顿求解和滑窗 BA，自适应权重在点稀少时增强线约束。
- RGB-D 模式下在 TUM Freiburg3 与 Replica 序列评估，ATE 分别降低 38.5% 和 30.1%。

**验证范围与局限**：验证限于 RGB-D 模式下的 22 个 TUM RGB-D Freiburg3 序列和 8 个 Replica 房间与办公室序列。

## 英文摘要 (Abstract)

Autonomous mobile robots in warehouses and production facilities operate in precisely the environments that defeat point-feature visual odometry: featureless aisles, uniform walls, repetitive racking and specular floors. Such environments are, however, rich in straight-edge structure: rack uprights, door frames, wall junctions and cabinet outlines present high-contrast linear edges stable across wide viewpoint changes. A line-feature extension to cuVSLAM, a CUDA-accelerated visual-SLAM system, is presented that recovers this signal. Lines are parameterised as Plücker coordinates for geometric transport and as the minimal 4-DOF orthonormal representation of Bartoli and Sturm for optimisation; a Cauchy-robust point-to-line residual with analytic Jacobians is folded directly into cuVSLAM's per-frame Gauss-Newton pose solve, and the same line state is jointly refined in the Schur-complement sliding-window bundle adjustment. An adaptive information weight causes lines to assume more of the estimation burden exactly as point features become scarce, and the extension adds residual blocks to existing solvers rather than introducing a second estimator, reducing exactly to the unmodified point pipeline when disabled. Evaluated in RGB-D mode under SE(3) Umeyama alignment with no scale correction, line features reduce mean absolute trajectory error by 38.5% over the 22 sequences of the TUM RGB-D Freiburg3 collection and by 30.1% over the 8 Replica room and office sequences, where median translation error falls by 38.9% and median rotation error by 66.4%, with zero tracking failures in any configuration tested.

作者：Dara Molloy, Terry Wu, Wonju Lee, Abhilash Nand Kumar, David Adley, Conor Ferguson, Hesam Rabeti
:::

## 原始参考来源 (Sources)

- [arXiv 2610.20958：Line-Augmented cuVSLAM: Robust Visual Odometry in Low-Texture Environments](https://arxiv.org/abs/2610.20958)