3 accepted papers
This paper focuses on high-performance robotic contour tracking under the uncertainties that commonly exist in actual robotic applications. These uncertainties can be attributed to the robot itself (such as modeling errors or mechanical defects like backlash) or to environmental issues (such as cali
This work employs an adaptive learning mechanism to perform tracking of an unknown object through RGBD cameras. We extend our previous framework to robustly track a wider range of arbitrarily shaped objects by adapting the model to the measured object size. The size is estimated as the object underg
Visual tracking of unknown objects is an essential task in robotic perception, of importance to a wide range of applications. In the general scenario, the robot has no full 3D model of the object beforehand, just the partial view of the object visible in the first video frame. A tracker with this in…