license: cc0-1.0
task_categories:
- tabular-classification
tags:
- robotics
- terrain-classification
- field-robotics
pretty_name: BorealTC
Dataset Card for BorealTC
This dataset contains IMU and wheel timeseries of data recorded with a Husky A200 UGV. It was recorded on five different types of terrains: snow, ice, silty loam, asphalt, flooring.
Dataset Details
Dataset Description
Recorded with a Husky A200 wheeled UGV, BorealTC contains 116 min of Inertial Measurement Unit (IMU), motor current, and wheel odometry data, focusing on typical boreal forest terrains, notably snow, ice, and silty loam. The dataset also includes experiments on asphalt and flooring. All runs were recorded in ForΓͺt Montmorency and on the main campus of UniversitΓ© Laval, Quebec City, Quebec, Canada.
- Curated by: Northern Robotics Laboratory, UniversitΓ© Laval, QuΓ©bec, Canada
- License: CC0 1.0 Universal
Dataset Sources
- Repository: norlab-ulaval/BorealTC
- Paper: 10.1109/IROS58592.2024.10801407
- Page: BorealTC
Uses
This data was intended for terrain classification problems.
Direct Use
This dataset could be used as example data for sensor timeseries processing.
Dataset Structure
Each folder contains data for runs recorded on a specific terrain class. The data for each run is included in two CSV files: imu_*.csv and pro_*.csv:
borealtc
βββ CLASS1
β βββ imu_00.csv
β βββ imu_01.csv
β βββ ...
β βββ pro_00.csv
β βββ pro_01.csv
β βββ ...
βββ CLASS2
βββ imu_00.csv
βββ imu_01.csv
βββ ...
βββ pro_00.csv
βββ pro_01.csv
βββ ...
Each imu file contains IMU-recorded rotational velocities and linear accelerations.
time,wx,wy,wz,ax,ay,az
0.0,0.0015195721884953,0.0040130227245162,-0.0070785057037968,1.4258426214785636,-0.0832771308374386,9.609228803438713
...
Each pro file contains motor currents and wheel velocities recorded by the wheel service of the Husky.
time,curL,curR,velL,velR
0.0,1.78,2.57,0.0236220472440944,0.0236220472440944
...
Dataset Creation
Curation Rationale
This dataset aims at collecting terrain data on terrains typical of boreal forests.
Data Collection and Processing
This dataset was recorded with a Husky A200 wheeled UGV on five terrains.
Citation
BibTeX:
@inproceedings{LaRocque2024,
title = {{Proprioception Is All You Need: Terrain Classification for Boreal Forests}},
url = {http://dx.doi.org/10.1109/IROS58592.2024.10801407},
doi = {10.1109/iros58592.2024.10801407},
booktitle = {2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
publisher = {IEEE},
author = {LaRocque, Damien and Guimont-Martin, William and Duclos, David-Alexandre and Giguère, Philippe and Pomerleau, Fran\c{c}ois},
year = {2024},
month = oct,
pages = {11686β11693}
}
Contributions
Thanks to @WillGuimont and @Asers387 for the help in curating this dataset.