Abstract
This paper describes an image processing system developed for automatic counting the number of collembola individuals on petri disks images. The system uses image segmentation and mathematical morphology techniques to identify and count the number of collembolans. The main challenges are the specular reflections at the edges of the circular samples and the foam present in a number of samples. The specular reflections are efficiently identified and removed by performing a two-stage segmentation. The foam is considered to be noise, as it is at cases difficult to discriminate between the foam and the collembola individuals. Morphological image processing tools are used both for noise reduction and for the identification of the collembolans. A total of 38 samples (divided in 3 groups according to their noise level) were tested and the results produced from the automatic system compared to the values available from manual counting. The relative error was on average 5.0% (3.4% for good quality samples, 4.6% for medium quality and 7.5% for poor quality samples).

Abstract
In this paper, we propose an algorithm that combine the restriction on motor's velocities and the kinematic model of Omni-Directional mobile robots to improve the trajectory's following. The algorithm verifies the reference velocities of the robot and redefine them if necessary, in order to prevent possible saturation on motor's velocities. Simulation results of the algorithm applied to an omnidirectional mobile robot are presented. Copyright © 2006 IFAC.

Abstract
This paper presents the experimental identification of the model's parameters of an omni-directional mobile robot with four wheels. The parameters related to dynamic equations are the viscous frictions, the coulomb frictions and the inertia moment of the robot. Two methods of parameters identification are described. A simulation environment and simulation results are presented. Copyright © 2006 IFAC.

Abstract
This paper presents an automated method for the segmentation of the vascular network in retinal images. The algorithm starts with the extraction of vessel centerlines, which are used as guidelines for the subsequent vessel filling phase. For this purpose, the outputs of four directional differential operators are processed in order to select connected sets of candidate points to be further classified as centerline pixels using vessel derived features. The final segmentation is obtained using an iterative region growing method that integrates the contents of several binary images resulting from vessel width dependent morphological filters. Our approach was tested on two publicly available databases and its results are compared with recently published methods. The results demonstrate that our algorithm outperforms other solutions and approximates the average accuracy of a human observer without a significant degradation of sensitivity and specificity.

Abstract

Abstract
This paper presents a new architecture for coordinating multiple autonomous robots in the execution of cooperative tasks. The architecture is based on the definition of a strategy that uses different tactics, setplays and roles. Roles enable to configure individual behaviour by performing specific tasks using a given set of actions. The proposed architecture allows flexible and efficient multi-robot operation in dynamic environments. The paper also presents an application of the proposed architecture to a complex domain such as middle-size robotic soccer. Our architecture is also generally enough to be applied in different robotic soccer leagues and similar multi-robot problems. Copyright © 2006 IFAC.