Data coverage
The FoMo dataset is a multi-season collection recorded in a boreal forest environment, featuring deep snow, off-road terrain, steep slopes, and highly variable weather. It provides synchronized multi-modal sensor data—including two lidars (RoboSense and Leishen), an FMCW radar (Navtech), stereo and monocular cameras, dual IMUs, wheel odometry, power data, calibration sequences, and precise ground-truth trajectories via GNSS-PPK fusion. Designed to support research on robust robot autonomy under adverse conditions, FoMo includes repeated traversals of six trajectories of varying complexity for long-term SLAM and odometry evaluation, as well as rich metadata such as one-minute weather station measurements. The dataset is intended to challenge state-of-the-art SLAM, localization, traversability analysis, and multi-season robotics research.
Access & permitted use
Review the publisher’s documentation for availability, eligibility and permitted uses, including commercial analysis, model training and redistribution.
Creative Commons Attribution 4.0 International (CC BY 4.0). See https://creativecommons.org/licenses/by/4.0/
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