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Communication Dans Un Congrès Année : 2022

Localization of autonomous vehicle with low cost sensors

Résumé

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.
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Mohamad Albilani, Amel Bouzeghoub. Localization of autonomous vehicle with low cost sensors. 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS), Oct 2022, Denver, United States. pp.339-345, ⟨10.1109/MASS56207.2022.00056⟩. ⟨hal-03915421⟩
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