High-definition 3D map for autonomous vehicles in Vietnam: A comparison between graph simultaneous localization and mapping and the normal distributions transform algorithm

Abstract

Autonomous vehicles have a fundamental part to play in future transportation. In order to work, such vehicles need a way of determining their exact location. To date, two techniques have proved applicable: geolocation using GPS and 3D mapping. In the latter case, the creation of the 3D map is an essential step in preparing the software. This manuscript presents a novel method for creating a high-definition 3D map using a Velodyne sensor. The primary objective is to achieve deeper understanding of the map creation algorithm and to lay the groundwork for future autonomous vehicle architecture. In this manuscript, two high-definition mapping algorithms are applied: the graph simultaneous localization and mapping algorithm and the normal distributions transform algorithm. The results of both displayed different strengths and weaknesses upon creating a high-definition 3D map, which may help other researchers to select the best algorithm in future.