Real-Time Model-Based Monocular Pose Tracking for an Asteroid by Contour Fitting

Abstract

This article presents an innovative framework of real-time vision-based pose tracking for asteroid using the contour information of the asteroid image. At the first-time instant, the tracking is initialized by the distance-based template matching and contour-based pose optimization. Subsequently, at each time instant, with the prediction of the extended Kalman filter (EKF) as initial guess, the pose of the asteroid is obtained in real time by geometrically fitting the contour of the projected asteroid CAD model over the contour of the asteroid image with M-estimation. The variance of the pose is calculated based on 1-order approximation inference, which enables EKF to generate the final pose estimation and predict the pose at the next time instant. Sufficient experiments validate the accuracy and the efficiency of the proposed method.