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Kalman Filters for Embedded Sensors by nicolagiacobbe is a document available to read on EtoBox.
This study presents a methodology for improving the estimation of physical values using Kalman filters and multi-physical models in embedded sensors, focusing on low power consumption and real-time processing. The methodology is illustrated through a 2D orientation estimation problem using an inertial measurement unit on a low power microcontroller, achieving promising results with minimal CPU usage. The paper discusses the technical background, the application of Kalman filters, and the implications for au
- Author
- nicolagiacobbe
- Language
- EN