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The NavINST Dataset for Multi-Sensor Autonomous Navigation

Description: This is a comprehensive multi-sensory dataset from various road trajectories in Kingston, ON, and Calgary, AB, Canada. This dataset features diverse lighting conditions and includes data from two indoor garages, with corresponding 3D maps. The dataset includes data from multiple commercial-grade IMUs and a tactical-grade IMU, along with a wide range of perception sensors. Notably, it is one of the first datasets to feature a solid-state LiDAR, alongside a mechanical LiDAR, four electronically scanning RADARs, a monocular camera, and two stereo cameras. Additionally, the dataset contains forward speed measurements from the vehicle's odometer and accurately post-processed high-end GNSS/IMU data, providing precise ground truth positioning and navigation information. The NavINST dataset is designed to facilitate advanced research in high-precision positioning, navigation, mapping, computer vision, and multi-sensor fusion, offering rich data for developing and validating robust autonomous vehicle algorithms. Finally, the dataset is fully integrated with ROS to ensure ease of use and accessibility for the research community. It also includes a toolkit for users working offline.
Authors: Marques de Araujo, Paulo Ricardo; Queen's University; ORCID iD 0000-0002-8027-5578
Mounier, Eslam; Queen's University; Ain Shams University; ORCID iD 0000-0002-7020-2842
Bader, Qamar; Queen's University; ORCID iD 0000-0002-4667-1710
Dawson, Emma; Queen's University; ORCID iD 0000-0002-8321-5124
Ismail Kaoud Abdelaziz, Shaza; Queen's University; ORCID iD 0000-0002-5664-5735
Elhabiby, Mohamed; Ain Shams University; ORCID iD 0000-0002-1909-7506
Noureldin, Aboelmagd; Royal Military College of Canada; Queen's University; ORCID iD 0000-0001-6614-7783
Keywords: Autonomous vehicles
multi-sensor system dataset
indoor navigation
urban navigation
solid-state lidar
3D maps
Field of Research: 
Industrial, systems and processes engineering
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Other industrial, systems and processes engineering
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Other industrial, systems and processes engineering
Publication Date: 2024-11-18
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
Funder: Natural Sciences and Engineering Research Council; RGPIN-2020-03900
Natural Sciences and Engineering Research Council; ALLRP-560898-20
URI: https://doi.org/10.20383/103.01089
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
Marques de Araujo, P., Mounier, E., Bader, Q., Dawson, E., Ismail Kaoud Abdelaziz, S., Elhabiby, M., Noureldin, A. (2024). The NavINST Dataset for Multi-Sensor Autonomous Navigation. Federated Research Data Repository. https://doi.org/10.20383/103.01089