PERANCANGAN MAPPING PADA AUTONOMOUS ELECTRIC VEHICLE BERBASIS LIDAR MENGGUNAKAN ALGORITMA SLAM

WIJAYA, PATRICK KUSUMA and Husin, Zaenal (2022) PERANCANGAN MAPPING PADA AUTONOMOUS ELECTRIC VEHICLE BERBASIS LIDAR MENGGUNAKAN ALGORITMA SLAM. Undergraduate thesis, Sriwijaya University.

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Abstract

Autonomous electric vehicles require the ability to recognize their surroundings through mapping. The purpose of the mapping is to provide directions when driving in new locations and uncharted areas. However, the current method used is still not able to map well, so in this research, mapping is carried out using SLAM (Simultaneous Localization and Mapping). In this study, Hector SLAM is used as an algorithm for mapping. Hector SLAM is an algorithm that maps based on data generated by sensors; this study uses the RPLidar A3 sensor as the main sensor. In this study, testing was carried out on two routes, namely the route of Sriwijaya University Palembang campus and Indralaya campus. To see the accuracy of the method used, a comparison was made with the map from Google Maps. On the Palembang campus route, the route is divided into four points, namely point A, B, C, and D. The A-B route is the route that gets the highest accuracy, being 85.7% accurate. Meanwhile, for the testing on the Indralaya route, an additional route was added which had a building closer to the road. This route is also divided into points, namely point A, B, C, D, and E. Testing on the C-E route gives the highest accuracy, being 83.6% accurate. The overall results of this study indicate that this algorithm can be used in autonomous electric vehicles.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Autonomous Electric Vehicle, RPLidar, Hector SLAM
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Patrick Kusuma Wijaya
Date Deposited:	26 Jul 2022 04:23
Last Modified:	26 Jul 2022 04:23
URI:	http://repository.unsri.ac.id/id/eprint/74734

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