Vision-Based Pose Estimation of Quadcopters using UKFs
نویسنده
چکیده
A 12-state dynamical model of a quadcopter is detailed. A vision-based measurement model is implemented for full state estimation of the quadcopter, with traditional translation and rotation measurement models used for comparison. An Unscented Kalman Filter using van der Merwe sigma point weights is implemented, and analysis of the vision-based estimator is conducted under varying measurement intervals. Measurement fusion from multiple cameras is used to improve estimation errors and covariances.
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