Histograms-based Visual Servoing

Quentin Bateux 1 Eric Marchand 1
1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA_D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : In the direct visual servoing methods such as pho-tometric framework, the images as a whole are used to define a control law. This can be opposed to the classical visual servoing approaches that relies on geometric features and where image processing algorithms that extract and track visual features are necessary. In this paper, we propose a generic framework to consider histogram as a visual feature. A histogram is an estimate of the probability distribution of a variable (for example the probability of occurrence in an intensity, color, or gradient orientation in an image). We show that the framework we proposed applies, but is not limited to, a wide set of histograms and allows the definition of efficient control laws. Statistical comparisons are presented from simulation results and real robots experiments including navigation tasks are also provided.
Type de document :
Article dans une revue
IEEE Robotics and Automation Letters, IEEE 2017, 2 (1), pp.80-87
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  • HAL Id : hal-01265560, version 1


Quentin Bateux, Eric Marchand. Histograms-based Visual Servoing. IEEE Robotics and Automation Letters, IEEE 2017, 2 (1), pp.80-87. 〈hal-01265560〉



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