The aim of the work is to determine the best landmark for its use in tasks such as precise positioning of AGVs or mobile robots in front of loading/unloading areas. The work developed aims at determining the precision that can be achieved with different pattern landmarks, of use in positioning systems, based on computer vision. Different computer vision algorithms have been tested from the images acquired from different camera configurations and bending angles with respect to the vertical axis. As a result of the evaluation of these errors, we extract the recommendation of the most favourable bicolour pattern to be used, as well as the bounding errors obtained from the segmentation and recognition methods most frequently used.

We analyze the problem of local thresholding of a scene under the constraint of the geometric model of the target to be located, in the scope of the locating search process of an essentially-binary target in a gray-level scene. An optimal threshold is obtained which maximizes the fitting of the thresholded image to the target model template in the binary domain. As a result of this maximizing process the Kolmogorov-Smirnov similarity measure is obtained, which allows target spatial location in the scene with no need of explicit thresholding of the image, and avoids the high computing cost associated to gray-level domain similarity measures, such as normalized correlation. When used as a similarity measure, the nonparametric characteristic of the Kolmogorov-Smirnov statistic yields invariance and normalizing properties, which are shown to improve the properties of commonly-used gray-level domain similarity measures.

A robotic system developed to manipulate ophthalmic lenses during the edging process is presented. The robot is assisted by a machine vision system to accurately determine the position and orientation of the lens' optical center and axis, through the localization of two small fiducial marks on the lens surface. The optimal design of the fiducial marks is investigated in order to minimize their size. It is shown that a regular diamond is the most detectable shape at minimum sizes. Three different camera placement strategies are discussed, taking into account accuracy constraints and calibration requirements. The chosen solution uses a camera attached to the robot end-effector. The robotic system proves to be advantageous with respect to the manual process, substantially improving the final accuracy while maintaining or even reducing the cycle time.