Identification of a scaled-model riser dynamics through a combined computer vision and adaptive Kalman filter approach
A projective geometry computer vision method maps object space into image space. Image coordinates were obtained through a mathematical morphology base algorithm. A compliant mechanism and a Lagrangian formulation was employed to model the riser. A Kalman filter used image coordinates to identify riser dynamics and a forcing term.
riser dynamics computer vision compliant mechanisms shaping filter non-linear adaptive kalman filter