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

arXiv: https://arxiv.org/abs/2601.19557 · HTML: https://mlsanity.com/paper/2601.19557/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 48 references that are in the map.
- First posted on arXiv 27 Jan 2026.

## Builds on (most cited first, 18 of 18)

- [VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator](https://mlsanity.com/paper/1708.03852/) (2017)
- [The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset](https://mlsanity.com/paper/1909.01300/) (2019)
- [4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving](https://mlsanity.com/paper/2009.06364/) (2020)
- [A General Optimization-based Framework for Global Pose Estimation with Multiple Sensors](https://mlsanity.com/paper/1901.03642/) (2019)
- [M2DGR: A Multi-sensor and Multi-scenario SLAM Dataset for Ground Robots](https://mlsanity.com/paper/2112.13659/) (2021)
- [SubT-MRS Dataset: Pushing SLAM Towards All-weather Environments](https://mlsanity.com/paper/2307.07607/) (2023)
- [General Place Recognition Survey: Towards Real-World Autonomy](https://mlsanity.com/paper/2405.04812/) (2024)
- [BotanicGarden: A High-Quality Dataset for Robot Navigation in Unstructured Natural Environments](https://mlsanity.com/paper/2306.14137/) (2023)
- [The Hilti SLAM Challenge Dataset](https://mlsanity.com/paper/2109.11316/) (2021)
- [S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAM](https://mlsanity.com/paper/2210.13723/) (2022)
- [Challenges of SLAM in extremely unstructured environments: the DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset](https://mlsanity.com/paper/2207.06815/) (2022)
- [VSLAM-LAB: A Comprehensive Framework for Visual SLAM Methods and Datasets](https://mlsanity.com/paper/2504.04457/) (2025)
- [GO: The Great Outdoors Multimodal Dataset](https://mlsanity.com/paper/2501.19274/) (2025)
- [GPGM-SLAM: a Robust SLAM System for Unstructured Planetary Environments with Gaussian Process Gradient Maps](https://mlsanity.com/paper/2109.06596/) (2021)
- [Challenges of Indoor SLAM: A multi-modal multi-floor dataset for SLAM evaluation](https://mlsanity.com/paper/2306.08522/) (2023)
- [The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhouse](https://mlsanity.com/paper/2402.00438/) (2024)
- [Are We Ready for Planetary Exploration Robots? The TAIL-Plus Dataset for SLAM in Granular Environments](https://mlsanity.com/paper/2404.13600/) (2024)
- [DiTer++: Diverse Terrain and Multi-modal Dataset for Multi-Robot SLAM in Multi-session Environments](https://mlsanity.com/paper/2412.05839/) (2024)

## Built on by (most cited first, 1 of 1)

- [Visual Relocalization from Sparse Views in Aliased and Low-Texture Environments via Novel View Synthesis](https://mlsanity.com/paper/2607.22147/) (2026)

## Abstract (arXiv)

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.