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- W4312304893 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." @default.
- W4312304893 created "2023-01-04" @default.
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- W4312304893 date "2022-10-01" @default.
- W4312304893 modified "2023-09-23" @default.
- W4312304893 title "Localization of Autonomous Vehicle with low cost sensors" @default.
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- W4312304893 doi "https://doi.org/10.1109/mass56207.2022.00056" @default.
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