Tesis de Grado a Ingeniería Electromecánica con énfasis en Electrónica - Hernandarias - 2019

Title:
Fusión de sensores para estimar la orientación de un vehículo autónomo a escala, mediante el Filtro de Kalman.

Author:
Erid Pacheco [email protected]

Tutor:
Ariel Guerrero [email protected]

Summary:
The fusion of sensors was carried out in order to obtain precise estimates of the orientation for the correct navigation of an autonomous vehicle at scale. The project was framed in the experimental design, with a quantitative approach at a comprehensive level. Mathematical tools were used as techniques and data collection instruments that allowed determining the noise properties of the sensors to be implemented in the Kalman filter. For the elaboration of the project and fulfillment of the objectives, a myrio (embedded device of the National Instruments company) was used as the data processing tool, LabVIEW as software for the implementation and Matlab (another support) for the analysis of data. In fact, calibration methods were developed (for the accelerometer and gyroscope) with a practical approach, so that it can be implemented before the start of the race in real time and for the case of the accelerometer the Kalman filter was used for the purposes of obtain the scale factor correction matrix and axis misalignment. Likewise, simulations were developed and the influence of the change of the parameters involved in the Kalman filter equations could be determined, and undesired effects such as distortions in the magnetic field, which generate variations in the reading of the sensors, were reduced, which lead to an incorrect estimation of the orientation and therefore in an incorrect navigation. In this way it was possible to conclude that the results were very effective and the proposed objectives were met, since errors were kept within the established bounds for the desired purpose (error less than two meters along the route of the autonomous car to scale).
Keywords: Kalman filter. Sensor fusion.

Pacheco Viana, Erid Eulogio. (2019); Fusión de sensores para estimar la orientación de un vehículo autónomo a escala. Alto Paraná, Universidad Católica. 140 p.
Tutor: Lic. Gregorio Ariel Guerrero Moral.
Defensa de Proyecto de Fin de Carrera
Palabras clave: Fusión de sensores. Filtro de Kalman.