Filtro de kalman estendido baseado em quaternions para estimação de um sistema de 6–dof embarcado

Abstract

This work proposes the implementation of an Extended Kalman Filter to estimate the orientation and position of a six degrees of freedom (6–DOF) rigid body embedded in an FPGA with a commercial processor. The approach used to parameterize the dynamics of the rigid body was by Quaternions, which, because they have a particular function for three dimensional rotations, provide an alternative to traditional Euler angles, reducing the computational effort involved, as well as the Gimbal Lock problem, that occurs when there are singularities in the rotation matrices. To validate the estimator, a Stewart Platform was used, equipped with an accelerometer, a gyroscope and a camera. Although this work considers the use of common low-cost sensors and the use of markers with simple geometry, the results show excellent performance of the developed filter, being able to estimate the position and orientation with an error below 8.14 mm and 0.63o, respectively. Furthermore, the effectiveness of the approach has also been evaluated, showing that the filter is able to converge quickly when the markers are retrieved after a loss of camera data for a short period of time.