Localization of an Autonomous Vehicle in Conditions of Poor GPS Signal

Student: Guzhva Nikita

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Infocommunication Technologies and Systems (Bachelor)

Final Grade: 8

Year of Graduation: 2020

The goal of this work is to improve the accuracy of vehicle positioning, using a limited set of sensors and a map in conditions of poor GPS-signal. The considered vehicle is a city tramway. In the course of this work, an analysis of existing approaches and methods for localizing autonomous vehicles and robots was performed. According to the results of this research it was decided to take the particle filter and Kalman filter as the basis for the original algorithm. The implementation of the method described in this paper was carried out in the C ++ programming language with the active usage of the OpenCV library. The experimental results demonstrate that under different conditions with varying degrees of difficulty, the software copes with the task smoothly and shows the localization accuracy of up to 2 meters.

Full text (added May 18, 2020)

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