%0 Journal Article
%A Diosi, Albert
%A Šegvić, Siniša
%A Remazeilles, Anthony
%A Chaumette, François
%T Experimental evaluation of autonomous driving based on visual memory and image-based visual servoing
%D 2011
%@ 1524-9050
%U https://hdl.handle.net/11556/4095
%X In this paper, the performance of a topological-metric visual-path- following framework is investigated in different environments. The framework relies on a monocular camera as the only sensing modality. The path is represented as a series of reference images such that each neighboring pair contains a number of common landmarks. Local 3-D geometries are reconstructed between the neighboring reference images to achieve fast feature prediction. This condition allows recovery from tracking failures. During navigation, the robot is controlled using image-based visual servoing. The focus of this paper is on the results from a number of experiments that were conducted in different environments, lighting conditions, and seasons. The experiments with a robot car show that the framework is robust to moving objects and moderate illumination changes. It is also shown that the system is capable of online path learning.
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