首个专用于评估RTK-SLAM绝对精度的地理参考数据集，揭示传统方法会严重低估误差。
An RTK-SLAM Dataset for Absolute Accuracy Evaluation in GNSS-Degraded Environments
- 用全站仪独立获取真实坐标，避免GNSS作真值导致的偏差
- 在室内环境下RTK-SLAM仍保持分米级全局精度，而纯RTK退化至十米级
- 发现标准对齐方法可使定位误差被低估高达76%，适合导航与测绘研究者
RTK-SLAM系统融合实时动态（RTK）GNSS定位与同时定位与地图构建（SLAM），有望实现相对一致性与全局坐标参考，适用于高效地理参照测绘。然而，当前主流评估指标绝对轨迹误差（ATE）先通过最优刚性变换对齐估计轨迹与参考轨迹，再计算误差。这种SE(3)对齐会吸收全局漂移和系统性误差，使轨迹看似更准确，无法真实反映RTK-SLAM的全局精度。本文提出一个地理参照数据集与评估方法，揭示此差距。核心设计原则是：仅将RTK接收器作为系统输入，而真值由大地测量全站仪独立建立，这一分离机制在现有数据集中均不存在——多数以GNSS为部分真值。数据集采用手持式RTK-SLAM设备采集，包含两个场景。我们评估了激光-惯性、视觉-惯性及激光-视觉-惯性型RTK-SLAM系统，并与独立的RTK系统对比，直接报告全局精度与经SE(3)对齐后的相对精度，以凸显差异。结果表明，SE(3)对齐可能使绝对定位误差被低估达76%。在开阔天空下，RTK-SLAM达到厘米级绝对精度；在室内，仍维持分米级全球精度，而独立RTK则退化至数十米。数据集、标定文件与评估脚本已公开于 https://rtk-slam-dataset.github.io/。
原文摘要 · Abstract (English)
RTK-SLAM systems integrate simultaneous localization and mapping (SLAM) with real-time kinematic (RTK) GNSS positioning, promising both relative consistency and globally referenced coordinates for efficient georeferenced surveying. A critical and underappreciated issue is that the standard evaluation metric, Absolute Trajectory Error (ATE), first fits an optimal rigid-body transformation between the estimated trajectory and reference before computing errors. This so-called SE(3) alignment absorbs global drift and systematic errors, making trajectories appear more accurate than they are in practice, and is unsuitable for evaluating the global accuracy of RTK-SLAM. We present a geodetically referenced dataset and evaluation methodology that expose this gap. A key design principle is that the RTK receiver is used solely as a system input, while ground truth is established independently via a geodetic total station. This separation is absent from all existing datasets, where GNSS typically serves as (part of) the ground truth. The dataset is collected with a handheld RTK-SLAM device, comprising two scenes. We evaluate LiDAR-inertial, visual-inertial, and LiDAR-visual-inertial RTK-SLAM systems alongside standalone RTK, reporting direct global accuracy and SE(3)-aligned relative accuracy to make the gap explicit. Results show that SE(3) alignment can underestimate absolute positioning error by up to 76\%. RTK-SLAM achieves centimeter-level absolute accuracy in open-sky conditions and maintains decimeter-level global accuracy indoors, where standalone RTK degrades to tens of meters. The dataset, calibration files, and evaluation scripts are publicly available at https://rtk-slam-dataset.github.io/.
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