发布多模态行星环境SLAM数据集，助力机器人定位与地图构建。
The S3LI Vulcano Dataset: A Dataset for Multi-Modal SLAM in Unstructured Planetary Environments
- 在意大利火山岛采集视觉与激光雷达数据，覆盖多样地形与地貌。
- 包含多序列数据，支持定位、建图及场景识别算法的评测。
- 提供开源工具链，可生成真实位姿与标注样本，适合机器人研究者使用。
我们发布了S3LI Vulcano数据集，这是一个面向视觉与激光雷达模态的多模态数据集，旨在推动同时定位与建图（SLAM）及场景识别算法的发展与基准测试。数据在意大利西西里岛阿埃奥利群岛的维拉卡诺火山岛上采集，涵盖多种环境、纹理与地形，包括玄武岩或富铁岩石、老熔岩通道的地质构造，以及干燥植被和水体。数据可通过 rmc.dlr.de/s3li_dataset 获取，并配备开源工具包 github.com/DLR-RM/s3li-toolkit，用于生成真实位姿及准备场景识别任务的标注样本。
原文摘要 · Abstract (English)
We release the S3LI Vulcano dataset, a multi-modal dataset towards development and benchmarking of Simultaneous Localization and Mapping (SLAM) and place recognition algorithms that rely on visual and LiDAR modalities. Several sequences are recorded on the volcanic island of Vulcano, from the Aeolian Islands in Sicily, Italy. The sequences provide users with data from a variety of environments, textures and terrains, including basaltic or iron-rich rocks, geological formations from old lava channels, as well as dry vegetation and water. The data (rmc.dlr.de/s3li_dataset) is accompanied by an open source toolkit (github.com/DLR-RM/s3li-toolkit) providing tools for generating ground truth poses as well as preparation of labelled samples for place recognition tasks.
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