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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; 0000-0002-8027-5578 Mounier, Eslam; Queen's University; Ain Shams University; 0000-0002-7020-2842 Bader, Qamar; Queen's University; 0000-0002-4667-1710 Dawson, Emma; Queen's University; 0000-0002-8321-5124 Ismail Kaoud Abdelaziz, Shaza; Queen's University; 0000-0002-5664-5735 Elhabiby, Mohamed; Ain Shams University; 0000-0002-1909-7506 Noureldin, Aboelmagd; Royal Military College of Canada; Queen's University; 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 > Other industrial, systems and processes engineering > Other industrial, systems and processes engineering
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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