@inproceedings{8de5dd580de745ca926ccc18c8ac57cd,
title = "Localization of Autonomous Vehicle with low cost sensors",
abstract = "This paper presents the design and real-time validation of an Inertial Measurement Unit (IMU) and Global Positioning System (GPS) data fusion algorithm for real-time localization in an autonomous vehicle system. The data fusion method is based on a low-pass filter and the Error State Extended Kalman Filter (ES-EKF). In this paper, the system's hardware and software design are detailed. Real-time validation of the proposed method is presented using low-cost sensors. The algorithm is deployed and tested employing ground truth data on an embedded microcontroller, the STM32 Nucleo, and achieved a 92\% accuracy level on the road and proved reliable in actual industrial applications.",
keywords = "Autonomous Vehicles, Data fusion, error state extended kalman filter, low-pass filter",
author = "Mohamad Albilani and Amel Bouzeghoub",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 19th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022 ; Conference date: 20-10-2022 Through 22-10-2022",
year = "2022",
month = jan,
day = "1",
doi = "10.1109/MASS56207.2022.00056",
language = "English",
series = "Proceedings - 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "339--345",
booktitle = "Proceedings - 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2022",
}