Authors:
A. Durand Petiteville
;
M. Courdesses
and
V. Cadenat
Affiliation:
Université de Toulouse, UPS, INSA, INP, ISAE, LAAS, France
Keyword(s):
Visual servoing, Visual data estimation, Predictor/estimator pair.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Mobile Robots and Autonomous Systems
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
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.