Abstract
This paper describes the sensor and actuator modeling of a realistic wheeled mobile robot simulator The motivation of developing such simulator is to produce a personalized versatile tool that allows production and validation of robot software reducing considerably the development time. The mobile robot simulator was developed in Object Pascal with its dynamics based on the ODE (Open Dynamics Engine), allowing to develop robot software for a three wheel omnidirectional robot equipped with Infra-Red distance sensors and brushless motors.

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Abstract
Hand-geometry biometric recognition is normally based on the detection of five points that correspond to the fingertips and four points between them (valley points). Specific methods often have to be implemented during the acquisition stage to make the detection of those points easier. This study presents techniques that have been developed to overcome the difficulties and limitations of the current systems. Moreover, a hand-geometry based recognition system that has no constraints during image acquisition is presented. A methodology was developed based on the hand skeleton for the points on the fingertips and for the valley points it was based on the curvature of the hand contour. The principal difficulties were found during the segmentation step, which often fails if the fingers are not spread out. Once the points have been located, the necessary features for authentication were extracted. Classification algorithms were implemented at this stage. Those showing the best results presented a Genuine Acceptance Rate (GAR) of 76% and 8% for the False Acceptance Rate (FAR).

Abstract
In the last few years the research community has witnessed significant progress in biometric technology, due to the availability of a wide variety of databases. However, the available databases that are currently available present significant setbacks in terms of restricted access to data, low-resolution and restrictions imposed on individuals during the acquisition phase. In this paper, two new public databases are described that have been created, with fingerprint and palm print images and their characteristics are compared with other databases available in the research community. The advantages of these databases are the great variety of individual characteristics, they have no restrictions during acquisition and they have manual ground truth annotation. They were presented in two different international competitions and have been used in research by different authors.

Abstract
Omni-directional robots are becoming more and more common in recent robotic applications. They offer improved ease of maneuverability and effectiveness at the expense of increased complexity. Frequent applications include but are not limited to robotic competitions and service robotics. The goal of this work is to find a precise dynamical model in order to predict the robot behavior. Models were found for two real world omni-directional robot configurations and their parameters estimated using a prototype that can have 3 or 4 wheels. Simulations and experimental runs are presented in order to validate the presented work.

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