Diosi11a
A. Diosi, S. Segvic, A. Remazeilles, F. Chaumette. Experimental Evaluation of Autonomous Driving Based on Visual Memory and Image Based Visual Servoing. IEEE Trans. on Intelligent Transportation Systems, 12(3):870-883, September 2011.
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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 refer- ence 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 vi- sual servoing. The focus of this paper is on the results from a num- ber 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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BibTex Reference
@article{Diosi11a,
Author = {Diosi, A. and Segvic, S. and Remazeilles, A. and Chaumette, F.},
Title = {Experimental Evaluation of Autonomous Driving Based on Visual Memory and Image Based Visual Servoing},
Journal = {IEEE Trans. on Intelligent Transportation Systems},
Volume = { 12},
Number = {3},
Pages = {870--883},
Month = {September},
Year = {2011}
}
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