# SHIFT：用于 TSDF 的表面感知高速集成

> 原文链接：https://robotics.hellobike.com/papers/2026-09-06-2609-06547
> 频道：papers | 更新日期：2026-09-06 | 标签：arxiv, cs.RO
> 核心摘要：针对实时3D建图中距离场计算开销瓶颈，SHIFT利用3D深度几何压缩平坦区域并优化ESDF布局，在多种RGB-D和LiDAR序列上验证。

# SHIFT：用于 TSDF 的表面感知高速集成

::: v-pre
> 原文链接：[SHIFT: Surface-aware High-speed Integration For TSDFs](https://arxiv.org/abs/2609.06547)（arXiv 2609.06547 · 发布日期：2026-09-06）

**SHIFT: Surface-aware High-speed Integration For TSDFs**

针对实时3D建图中距离场计算开销瓶颈，SHIFT利用3D深度几何压缩平坦区域并优化ESDF布局，在多种RGB-D和LiDAR序列上验证。

## 核心要点

- 实时3D建图依赖ESDF进行在线运动规划，但高精度非投影距离场计算开销大。
- SHIFT从3D深度几何利用结构冗余，将平坦局部区域压缩为加权super-rays。
- 方法冻结平坦体素梯度，并用紧凑ESDF体素布局降低剩余波前内存占用。
- 在多种RGB-D和LiDAR序列评估，TSDF成本降低1.42到4.07倍，网格误差保持毫米级。

**验证范围与局限**：验证范围为多种RGB-D和LiDAR序列。

## 英文摘要 (Abstract)

Real-time 3D mapping is fundamental for autonomous robotic navigation, with Euclidean Signed Distance Fields (ESDFs) serving as the standard representation for online motion planning. While recent advancements in non- projective distance fields yield highly accurate maps, their computational overhead remains a severe bottleneck. Conventional integrators redundantly re-fuse millions of depth pixels every frame, even long after the corresponding voxels have converged, wasting significant computational resources in environments dominated by large planar surfaces. In this paper, we present SHIFT (Surface-aware High-speed Integration For TSDFs), an efficient mapping framework designed to reduce this per-frame update cost. By exploiting structural redundancy directly from 3D depth geometry, SHIFT compresses flat local regions into weighted super-rays and freezes flat-voxel gradients. A compact ESDF voxel layout further reduces the memory footprint of the remaining wavefront. Extensive evaluations across various RGB-D and LiDAR sequences show that SHIFT cuts TSDF cost by 1.42 to 4.07 times, while holding mesh error within millimeters, and reduces ESDF-layer memory by up to 28%

作者：Ayaan Choudhury, Lokender Tiwari
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## 原始参考来源 (Sources)

- [arXiv 2609.06547：SHIFT: Surface-aware High-speed Integration For TSDFs](https://arxiv.org/abs/2609.06547)