.png){kind=icon}
.png){kind=icon}
Return
Photometric Visual Servoing
.png){kind=icon}
OA
AI
DOI：10.1109/TRO.2011.2112593.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper proposes a new way to achieve robotic tasks by two-dimensional (2-D) visual servoing. Indeed, instead of using classical geometric features such as points, straight lines, pose, or a homography, as is usually done, the luminance of all pixels in the image is considered here. The main advantage of this new approach is that it requires no tracking or matching process. The key point of our approach relies on the analytic computation of the interaction matrix. This computation is based either on a temporal luminance-constancy hypothesis or on a reflection model so that complex illumination changes can be considered. Experimental results on positioning and tracking tasks validate the proposed approach and show its robustness to approximated depths, low-textured objects, partial occlusions, and specular scenes. They also showed that luminance leads to lower positioning errors than a classical visual servoing based on 2-D geometric visual features.
Keywords:
Cost function
optimization
photometry
visual features
visual servoing
Journal
IF:
10.5
Papers:
3.3K
Citations:
2.8W