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Improving mutual information based visual servoing

Amaury Dame 1 E. 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 a previous paper, we proposed a new way to achieve visual servoing. Rather than minimizing the error between the position of two set of geometric features, we proposed to maximize the mutual information shared by the current and desired images. This leads to a new information theoretic approach to visual servoing. Mutual information is a well known alignment function. Thanks to its robustness toward illumination variations, occlusions and multi modality, it has been widely used in medical applications for alignment as well as in general tracking problems. Despite those previous works, no highlight has been given on the problem of Hessian computation that yields, in the case of common approximations, to divergence of the optimization process. In this paper we focus on the need of computing the second order derivative of the mutual information in visual servoing. Experiments on a 6 dof robot demonstrates the significance of this works on visual servoing tasks.
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Submitted on : Thursday, December 9, 2010 - 12:14:46 AM
Last modification on : Thursday, January 20, 2022 - 4:13:12 PM
Long-term archiving on: : Thursday, June 30, 2011 - 1:41:37 PM


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  • HAL Id : inria-00544785, version 1


Amaury Dame, E. Marchand. Improving mutual information based visual servoing. IEEE Int. Conf. on Robotics and Automation, ICRA'10, 2010, Anchorage, Alaska, United States. pp.5531-5536. ⟨inria-00544785⟩



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