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MILUV: A Multi-UAV Indoor Localization dataset with UWB and Vision

Description: This dataset comprises 217 minutes of flight time over 36 experiments using three quadcopters, collecting ultra-wideband (UWB) ranging data such as the raw timestamps and channel-impulse response data, vision data from a stereo camera and a bottom-facing monocular camera, inertial measurement unit data, height measurements from a laser rangefinder, barometer data, magnetometer data, and ground-truth poses from a motion-capture system. The UWB data is collected from up to 12 transceivers affixed to mobile robots and static tripods in both line-of-sight and non-line-of-sight conditions. The UAVs flew at a maximum speed of 4.418 m/s in an obstacle-free indoor environment with visual fiducial markers as features.
Authors: Shalaby, Mohammed Ayman; McGill University; ORCID iD 0000-0002-6145-6509
Ahmed, Syed Shabbir; McGill University; ORCID iD 0009-0005-7459-3413
Dahdah, Nicholas; McGill University; ORCID iD 0009-0006-9846-7216
Cossette, Charles Champagne; McGill University; ORCID iD 0000-0002-9380-8361
Le Ny, Jerome; Polytechnique Montréal; ORCID iD 0000-0002-3417-4135
Forbes, James Richard; McGill University; ORCID iD 0000-0002-1987-9268
Keywords: Ultrawide-band radio
Vision
Localization
Multi-robot teams
Field of Research: 
Electrical engineering, computer engineering, and information engineering
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Systems control and automation
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Data-driven estimation, optimization, and control

Electrical engineering, computer engineering, and information engineering
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Systems control and automation
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Motion control of robots

Electrical engineering, computer engineering, and information engineering
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Communications and networks technologies
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Wireless communication systems

Electrical engineering, computer engineering, and information engineering
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Data analytics and signal processing
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Optimization and data analytics algorithms and systems
Publication Date: 2024-07-10
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
Funder: Natural Sciences and Engineering Research Council; NSERC Discovery and Alliance Grant
Canadian Foundation for Innovation; John R. Evans Leaders Fund
Denso Corporation
URI: https://doi.org/10.20383/103.0968
Related Identifiers: 
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Access to this dataset is subject to the following terms:
Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Citation
Shalaby, M., Ahmed, S., Dahdah, N., Cossette, C., Le Ny, J., Forbes, J. (2024). MILUV: A Multi-UAV Indoor Localization dataset with UWB and Vision. Federated Research Data Repository. https://doi.org/10.20383/103.0968