The S3LI Vulcano Dataset: A Dataset for Multi-Modal SLAM in Unstructured Planetary Environments

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Authors: Riccardo Giubilato, Marcus G. Muller, Marco Sewtz, L. González, John B. Folkesson, Rudolph Triebel
Cited by: 0

Abstract

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.

Fields of Study & Subjects

Robotics and Sensor-Based Localization 3D Surveying and Cultural Heritage Reinforcement Learning in Robotics

Publication details

Journal / source
arXiv (Cornell University)
Publication date
27 January 2026
Document type
Preprint