Diese Arbeit ist im Sonderforschungsbereich 531, "Computational Intelligence", der Universität Dortmund entstanden und wurde auf seine Veranlassung unter Verwendung der ihm von der Deutschen Forschungsgemeinschaft zur Verfügung gestellten Mittel gedruckt. Visual Servoing with Moments of SIFT FeaturesFrank Hoffmann, Thomas Nierobisch * , Torsten Seyffarth * and Günter Rudolph † * Chair for Control System Engineering/Electrical Engineering and Information Technology/University of Dortmund, Germany {frank.hoffmann, thomas.nierobisch, torsten.seyffarth}@uni-dortmund.de † Chair of systems analysis/Department of Computer Science/University of Dortmund, Germany guenter.rudolph@cs.uni-dortmund.deAbstract-Robotic manipulation of daily-life objects is an essential requirement in service robotic applications. In that context image based visual servoing is a means to position the end-effector in order to manipulate objects of unknown pose. This contribution proposes a 6 DOF visual servoing scheme that relies on the pixel coordinates, scale and orientation of SIFT features. The control is based on geometric moments computed over an alterable set of redundant SIFT feature correspondences between the current and the reference view. The method is generic as it does not depend on a geometric object model but automatically extracts SIFT features from images of the object. The foundation of visual servoing on generic SIFT features renders the method robust with respect to loss of redundant features caused by occlusion or changes in view point. The moment based representation establishes an approximate one-to-one relationship between visual features and degrees of motion. This property is exploited in the design of a decoupled controller that demonstrates superior performance in terms of convergence and robustness compared with an inverse image Jacobian controller. Several experiments with a robotic arm equipped with a monocular eye-in-hand camera demonstrate that the approach is efficient and reliable.

It is an important aim to reduce the cost of driver assistance systems to bring their benefit in safety and comfort to as many drivers as possible. A single camera used as an environmental sensor has the potential for a significant cost reduction. Based on the currently available camera and image processing technology this work evaluates how the portfolio of the camera based assistance systems can be expanded by an ACC function. By transferring the method of image-based controlling from robotic to distance control of vehicles, a known controller for radar systems is adapted to the characteristics of the camera. The detailed analysis of the resulting controller shows the influence of the controller parameters on different aspects of the system behavior.