SISTEM MAPPING PADA AUTONOMOUS INTELLIGENT VEHICLE DENGAN ALGORITMA FASTSLAM 2.0

YOGTA, ABENG and Suprapto, Bhakti Yudho and Dwijayanti, Suci (2020) SISTEM MAPPING PADA AUTONOMOUS INTELLIGENT VEHICLE DENGAN ALGORITMA FASTSLAM 2.0. Undergraduate thesis, Sriwijaya University.

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Abstract

Autonomous Intelligent Vehicles requires an accurate map to be able to move from the starting point to a autonomous destination. To form the map used the algorithm FastSLAM 2.0 using Monocular camera. This method was tested to form the environment map around the faculty of Engineering of Sriwijaya University campus Indralaya. The proposed method utilizes a recognizable road trait with the FCNN algorithm as an observation object from the algorithm FastSLAM 2.0. The implementation of this method successfully forms a map similar to Google Maps by using an observation model from FCNN that has 98.25% training accuracy and 71.082% test accuracy. A successfully formed map has IoU 0.159 against the map from Google Maps. The results are still not good but the map is already able to form a map with a route that corresponds to Google Maps.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	FastSLAM 2.0 (A Factored Solution to the Simultaneous Localization and Mapping), Autonomous Intelligent Vehicles, Mapping, Monocular, FCNN
Subjects:	Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL1-4050 Motor vehicles. Aeronautics. Astronautics
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Users 5753 not found.
Date Deposited:	08 May 2020 01:59
Last Modified:	08 May 2020 01:59
URI:	http://repository.unsri.ac.id/id/eprint/29223

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