一种用于GNSS退化环境中绝对精度评估的RTK-SLAM数据集
An RTK-SLAM Dataset for Absolute Accuracy Evaluation in GNSS-Degraded Environments
- Institute for Photogrammetry and Geoinformatics, University of Stuttgart（斯图加特大学摄影测量与地理信息学研究所）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出一个地质参考数据集和评估方法，揭示RTK-SLAM系统在绝对精度评估中的缺陷，通过分离RTK接收器与地面真实值，评估不同SLAM系统在开放天空和室内环境下的精度表现。
AI中文摘要：
RTK-SLAM系统集成了同时定位与建图(SLAM)与实时动态(GNSS)定位，承诺相对一致性和全球参考坐标以提高地理参考勘测效率。一个关键但被忽视的问题是，标准评估指标绝对轨迹误差(ATE)首先拟合估计轨迹与参考之间的最优刚体变换，再计算误差。这种所谓的SE(3)对齐吸收了全局漂移和系统误差，使轨迹看起来比实际更准确，并不适合评估RTK-SLAM的全局精度。我们提出一个地质参考数据集和评估方法，揭示这一差距。关键设计原则是RTK接收器仅作为系统输入，地面真实值通过测距总站独立建立。该数据集使用手持RTK-SLAM设备采集，包含两个场景。我们评估了LiDAR-惯性、视觉-惯性和LiDAR-视觉-惯性RTK-SLAM系统以及独立RTK，报告直接的绝对精度和SE(3)对齐的相对精度以明确差距。结果表明，SE(3)对齐可能低估绝对定位误差高达76%。RTK-SLAM在开放天空条件下实现厘米级绝对精度，在室内环境中保持分米级全局精度，而独立RTK在室内环境退化到数十米。数据集、校准文件和评估脚本可在https://rtk-slam-dataset.github.io/公开获取。
英文摘要：
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/.
