Experimental evaluation of autonomous driving based on visual memory and image-based visual servoing

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URI: https://hdl.handle.net/11556/4095
ISSN: 1524-9050
DOI: 10.1109/TITS.2011.2122334
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2011-09
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Abstract
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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Localization , mapping , path following , visual memory , visual servoing , Automotive Engineering , Mechanical Engineering , Computer Science Applications
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journal article
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Diosi , A , Šegvić , S , Remazeilles , A & Chaumette , F 2011 , ' Experimental evaluation of autonomous driving based on visual memory and image-based visual servoing ' , IEEE Transactions on Intelligent Transportation Systems , vol. 12 , no. 3 , 5740604 , pp. 870-883 . https://doi.org/10.1109/TITS.2011.2122334