https://github.com/ausmlab/yutomms
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
-
✓DOI references
Found 9 DOI reference(s) in README -
✓Academic publication links
Links to: mdpi.com -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (7.3%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: ausmlab
- License: other
- Language: HTML
- Default Branch: main
- Size: 3.12 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
YUTO MMS: A Comprehensive SLAM Dataset for Urban Mobile Mapping with Tilted LiDAR and Panoramic Camera Integration
The York University Teledyne Optech (YUTO) Mobile Mapping System (MMS) Dataset, encompassing four extensive sequences totalling 18.9 kilometres, was thoroughly assembled through two data collection expeditions on August 12, 2020, and June 21, 2019. Acquisitions were performed using a uniquely equipped vehicle, fortified with a panoramic camera, a tilted LiDAR, a Global Positioning System (GPS), and an Inertial Measurement Unit (IMU), journeying through two strategic locations: the York University Keele Campus in Toronto and the Teledyne Optech headquarters in City of Vaughan, Canada. This is a robust benchmark of prevailing Simultaneous Localization and Mapping (SLAM) systems. This dataset was created by a team of AUSM Lab.
For more details check out our paper, and website.
- Key Links
- YUTO MMS Dataset: Download
- Paper: "YUTO MMS: A Comprehensive SLAM Dataset for Urban Mobile Mapping with Tilted LiDAR and Panoramic Camera Integration"
- Models Code: MaverickProjectLidar2Image
- Website: YUTO MMS
Question Answering Datasets
- The YUTO MMS dataset contains questions:
- SLAM: PVL-Cartographer
Data Description
Datasets
- Sequence A: 324 m, one small loop.
- Sequence B: 7035 m, one large loop and a few small loops.
- Sequence C: 9137 m, many medium-size loops.
- Sequence D: 3634 m, a few loops.
Data Format
GNSS:
- IMU.csv:
ax, ay, az: acceleration.gx, gy, gz: angular rate.
- GPS.csv:
"latitude": ."longitude": . *"altitude": .
- IMU.csv:
Panoramic images: .jpg.
Lidar scans: .bin.
Data Statistics
YUTO MMS question decomposition datasets:
| Data | Image format and nubmer | LiDAR format and number | IMU+GPS format | |-----------|-------------------------|-------------------------|-------------------------| | Sequence A | .jpg, 700 | .bin, 1432 | .csv, 11845 | | Sequence B | .jpg, 8382 | .bin, 17395 | .csv, 143637 | | Sequence C | .jpg, 10778 | .bin, 22992 | .csv, 189875 | | Sequence D | .jpg, 4500 | .bin, 9615 | .csv, 79506 |
Reference
@article{doi:10.1177/02783649241261079,
author = {Yiujia Zhang and SeyedMostafa Ahmadi and Jungwon Kang and Zahra Arjmandi and Gunho Sohn},
title ={YUTO MMS: A comprehensive SLAM dataset for urban mobile mapping with tilted LiDAR and panoramic camera integration},
journal = {The International Journal of Robotics Research},
volume = {0},
number = {0},
pages = {02783649241261079},
year = {0},
doi = {10.1177/02783649241261079},
URL = {https://doi.org/10.1177/02783649241261079},
eprint = {https://doi.org/10.1177/02783649241261079}
}
YUTO MMS dataset is referenced here.
Owner
- Name: AUSMLab
- Login: ausmlab
- Kind: organization
- Location: Toronto, Ontario
- Website: https://ausmlab.com
- Repositories: 3
- Profile: https://github.com/ausmlab
Augmented Urban Space Modeling Lab @ York University
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1