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本数据集名为tiers-lidar-dataset-enhanced，由芬兰图尔库大学的图尔库智能嵌入式与机器人系统实验室创建。数据集包含9个序列，涵盖室内、室外和森林等多种环境，用于评估多模态激光雷达同步定位与地图构建（SLAM）算法。数据集通过集成高分辨率旋转和固态激光雷达，以及激光雷达相机和立体鱼眼相机，提供精确的地面实况数据。创建过程中，采用SLAM辅助的ICP基传感器融合方法生成地面实况地图，并通过自然分布变换（NDT）方法匹配实时点云数据。该数据集主要应用于自主驾驶和机器人导航领域，旨在解决在GNSS拒绝环境中的高精度定位问题。
The dataset evaluates algorithms' ability to align two Structure‑from‑Motion reconstructions under unknown relative pose and scale. It was built by recording multiple image sequences in a controlled indoor environment, using an ART‑2 tracking system to precisely track markers attached to the camera. A long sequence was processed with an offline incremental SfM pipeline to generate a scene point‑cloud and calibrate the transformation between the camera and tracker coordinate systems. Subsequently, twelve sequences were recorded in the tracked environment and processed with a keyframe‑based real‑time SLAM system.
