Abstract
This paper describes an estimator architecture for a Formula Student Prototype, based on data from an inertial measurement unit (IMU), a global positioning system (GPS), and from the underlying dynamic model of the car. A non-linear dynamic model of the car and realistic models for the sensors are presented. The estimates of attitude, rate-gyro bias, position, velocity and sideslip are based on Kalman filtering techniques. The resulting system is validated on a Formula Student prototype and assessed given ground truth data obtained by a set of differential GPS receivers installed onboard.
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Acknowledgments
This work was supported by FCT, through IDMEC, under LAETA, project UID/EMS/50022/2013. The authors thank the prompt and fruitful cooperation of the IST Formula Student team, FST Lisboa and ISR - Dynamical Systems and Ocean Robotics Lab, namely the assistance of Bruno Cardeira.
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Antunes, A., Cardeira, C., Oliveira, P. (2018). Application of Sideslip Estimation Architecture to a Formula Student Prototype. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_34
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DOI: https://doi.org/10.1007/978-3-319-70836-2_34
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