Improvements on Visual Servoing From Spherical Targets Using a Spherical Projection Model

This paper is concerned with improvements to visual feature modeling using a spherical projection model. Three spherical targets are considered: a sphere, a sphere marked with a tangent vector to a point on its surface, and a sphere marked with two points on its surface. A new minimal and decoupled set of visual features is proposed for each target using any central catadioptric camera. Using the proposed set for a sphere, a classical control law is proved to be globally asymptotically stable in the presence of modeling errors and locally asymptotically stable in the presence of calibration errors, considering that perspective and paracatadioptric cameras were used. Simulation and experimental results with perspective, paracatadioptric, and fish-eye cameras validate the proposed theoretical results.