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This papers deals with the problem of estimating the visual features during a vision-based navigation task when a temporary total occlusion occurs. The proposed approach relies on an existent specific algorithm. However, to be efficient, this algorithm requires highly precise initial values for both the image features and their depth. Thus, our objective is to design a predictor/estimator pair able to provide an accurate estimation of the depth value, even when the visual data are noisy. The obtained results show the efficiency and the interest of our technique.

proceedings of the 15th international conference on informatics in control, automation and robotics

A NEW PREDICTOR/CORRECTOR PAIR TO ESTIMATE THE VISUAL FEATURES DEPTH DURING A VISION-BASED NAVIGATION TASK IN AN UNKNOWN ENVIRONMENT - A Solution for Improving the Visual Features Reconstruction During an Occlusion