FoMo: A Multi-Season Dataset for Robot Navigation in Forêt Montmorency

Abstract

The Forêt Montmorency (FoMo) dataset is a comprehensive multi-season data collection, recorded over the span of one year in a boreal forest. Featuring a unique combination of on- and off-pavement environments with significant environmental changes, the dataset challenges established odometry and SLAM pipelines. Some highlights of the data include the accumulation of snow exceeding 1 m, significant vegetation growth in front of sensors, and operations at the traction limits of the platform. In total, the FoMo dataset includes over 64 km of six diverse trajectories, repeated during 12 deployments throughout the year. The dataset features data from one rotating and one hybrid solid-state lidar, a Frequency Modulated Continuous Wave (FMCW) radar, full-HD images from a stereo camera and a wide lens monocular camera, as well as data from two IMUs. Ground Truth is calculated by post-processing three GNSS receivers mounted on the Uncrewed Ground Vehicle (UGV) and a static GNSS base station. Additional metadata, such as one measurement per minute from an on-site weather station, camera calibration intrinsics, and vehicle power consumption, is available for all sequences. To highlight the relevance of the dataset, we performed a preliminary evaluation of the robustness of a lidar-inertial, radar-gyro, and a visual-inertial localization and mapping techniques to seasonal changes. We show that seasonal changes have serious effects on the re-localization capabilities of the state-of-the-art methods. The dataset and development kit are available at https://fomo.norlab.ulaval.ca.

Figures (14)

• Figure 1: FoMo dataset is a year-long recording capturing seasonal changes of a typical boreal forest.
• Figure 2: The UGV used for the data collection, equipped with tracks on snow (left) and wheels in other seasons (right).
• Figure 3: Circular view of daily average temperature and snow depth in meters over a year, from November 2024 to November 2025.
• Figure 4: An orthomosaic of Forêt Montmorency, the data recording site, with the six repeated trajectories colored by their label. From left to right, we can see Yellow, Red, Blue, Orange, Green, and Magenta. The lower-left inset shows the location of Forêt Montmorency within North America.
• Figure 5: Eight locations of interest captured in three modalities. The top row shows images captured from the left stereo camera. The second row shows radar scans warped into a Cartesian view. The third row shows point clouds from the RoboSense lidar colored by intensity. The fourth row shows the rear Basler camera rotated by 180°.