Self-calibrated visual servoing with respect to axial-symmetric 3D objects

Authors:
Duccio Fioravanti;Carlo Colombo;Benedetto Allotta
Affiliations:
University of Florence, Department of Energetics, Via di S.Marta 3, 50139 Florence, Italy;University of Florence, Department of Systems and Informatics, Via di S.Marta 3, 50139 Florence, Italy;University of Florence, Department of Energetics, Via di S.Marta 3, 50139 Florence, Italy
Venue:
Robotics and Autonomous Systems
Year:
2009

Citing 8
Cited 0

Direct Least Square Fitting of Ellipses

IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Calibration from Surfaces of Revolution

IEEE Transactions on Pattern Analysis and Machine Intelligence
Effect of Camera Calibration Errors on Visual Servoing in Robotics

The 3rd International Symposium on Experimental Robotics III
Multiple View Geometry in Computer Vision

Multiple View Geometry in Computer Vision
A Simple Technique for Improving Camera Displacement Estimation in Eye-in-Hand Visual Servoing

IEEE Transactions on Pattern Analysis and Machine Intelligence
Metric 3D Reconstruction and Texture Acquisition of Surfaces of Revolution from a Single Uncalibrated View

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image moments: a general and useful set of features for visual servoing

IEEE Transactions on Robotics
Continuous visual servoing despite the changes of visibility in image features

IEEE Transactions on Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

A self-calibrated approach to visual servoing with respect to non-planar targets modeled through a pair of coaxial circles plus one point is discussed. Full calibration data (fixed internal parameters) are obtained from two views, and used to recover the Euclidean structure of an auxiliary virtual plane associated to the target, together with the relative pose of the camera. Pose disambiguation is achieved without requiring any real third view of the target. The approach benefits of an off-line planning strategy by which the camera follows a 3D helicoidal path around an arbitrarily chosen axis. A convenient choice for the helicoidal axis is found to be that of the target axis itself. Simulation results demonstrate that the approach is robust with respect to noise both in the off-line and on-line control phases.