Title :
Statistically robust 2-D visual servoing
Author :
Comport, Andrew I. ; Marchand, Eric ; Chaumette, François
Author_Institution :
IRISA/INRIA, France
fDate :
4/1/2006 12:00:00 AM
Abstract :
A fundamental step toward broadening the use of real-world image-based visual servoing is to deal with the important issue of reliability and robustness. In order to address this issue, a closed-loop control law is proposed that simultaneously accomplishes a visual servoing task and is robust to a general class of image processing errors. This is achieved with the application of widely accepted statistical techniques such as robust M-estimation and LMedS. Experimental results are presented which demonstrate visual servoing tasks that resist severe outlier contamination.
Keywords :
closed loop systems; image motion analysis; least squares approximations; statistical analysis; LMedS; closed-loop control law; image processing errors; least median squares; real-world image-based visual servoing; robust M-estimation; severe outlier contamination resistance; statistical techniques; statistically robust 2D visual servoing; Computer errors; Error correction; Image processing; Pollution measurement; Resists; Robotics and automation; Robust control; Robustness; Target tracking; Visual servoing; Least median squares (LMedS); M-estimators; robust control law; visual servoing;
Journal_Title :
Robotics, IEEE Transactions on
DOI :
10.1109/TRO.2006.870666