Geo-referencing system for locating objects globally in LiDAR point cloud

Senapati, M. and Rajalakshmi, P. and et al, . (2020) Geo-referencing system for locating objects globally in LiDAR point cloud. In: IEEE World Forum on Internet of Things, WF-IoT 2020 - Symposium Proceedings, 2 June 2020 - 16 June 2020.

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Abstract

The LiDAR (Light detection and ranging) sensor is widely used to collect a three-dimensional view of the surrounding. This LiDAR's data is represented in the local East North Up (ENU) coordinate system and does not contain any global information. Converting this data into the global coordinate system will be helpful in intelligent transportation system (ITS) for object location tracking and sharing. This type of conversion is commonly known as geo-referencing. Generally, geo-referencing is used to associate a physical map or raster image with global locations in the field of Geographical Information System (GIS). In this paper, we have suggested a system for geo-referencing LiDAR point cloud, global positioning of objects present in the point cloud and sharing it with other communicating units present in the vehicular network. We have tested our system on data captured at the Indian Institute of Technology Hyderabad (IITH) campus and compared it with the manually collected GPS location of the objects. Our system is found to determine the global location of the objects with a sufficiently small error percentage of the order of 10-4.

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IITH Creators:
IITH CreatorsORCiD
Rajalakshmi, PUNSPECIFIED
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Co-ordinate system; Global coordinate systems; Global informations; Global positioning; Indian institute of technologies; Intelligent transportation systems; LIDAR (light detection and ranging); Vehicular networks
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 13 Jul 2021 05:29
Last Modified: 18 Feb 2022 06:33
URI: http://raiithold.iith.ac.in/id/eprint/8258
Publisher URL: http://doi.org/10.1109/WF-IoT48130.2020.9221162
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