|Visual Servoing Based on Efficient Histogram Information
Hajer Abidi*, Mohamed Chtourou, Khaled Kaaniche, and Hassen Mekki
International Journal of Control, Automation, and Systems, vol. 15, no. 4, pp.1746-1753, 2017
Abstract : "The robustness of a visual servoing task depends mainly on the efficiency of visual selections captured
from a sensor at each robot’s position. A task function could be described as a regulation of the values sent
via the control law to the camera velocities. In this paper we propose a new approach that does not depend on
matching and tracking results. Thus, we replaced the classical minimization cost by a new function based on
probability distributions and Bhattacharyya distance. To guarantee more robustness, the information related to
the observed images was expressed using a combination of orientation selections. The new visual selections are
computed by referring to the disposition of Histograms of Oriented Gradients (HOG) bins. For each bin we assign
a random variable representing gradient vectors in a particular direction. The new entries will not be used to
establish equations of visual motion but they will be directly inserted into the control loop. A new formulation of
the interaction matrix has been presented according to the optical flow constraint and using an interpolation function
which leads to a more efficient control behaviour and to more positioning accuracy. Experiments demonstrate the
robustness of the proposed approach with respect to varying work space conditions."
Global features, histogram of oriented gradients, mobile robot, visual servoing.