Abstract
Nowadays, there are many technologies that support location systems involving intrusive and nonintrusive equipment and also varying in terms of precision, range, and cost. However, the developers some time neglect the noise introduced by these systems, which prevents these systems from reaching their full potential. Focused on this problem, in this research work a comparison study between three different filters was performed in order to reduce the noise introduced by a location system based on RFID UWB technology with an associated error of approximately 18 cm. To achieve this goal, a set of experiments was devised and executed using a miniature train moving at constant velocity in a scenario with two distinct shapes-linear and oval. Also, this train was equipped with a varying number of active tags. The obtained results proved that the Kalman Filter achieved better results when compared to the other two filters. Also, this filter increases the performance of the location system by 15% and 12% for the linear and oval paths respectively, when using one tag. For a multiple tags and oval shape similar results were obtained (11-13% of improvement).

Abstract

Abstract
This paper reports on the creation of an interface for 3D virtual environments, computer-aided design applications or computer games. Standard computer interfaces are bound to 2D surfaces, e.g., computer mouses, keyboards, touch pads or touch screens. The Smart Object is intended to provide the user with a 3D interface by using sensors that register movement (inertial measurement unit), touch (touch screen) and voice (microphone). The design and development process as well as the tests and results are presented in this paper. The Smart Object was developed by a team of four third-year engineering students from diverse scientific backgrounds and nationalities during one semester. © 2014 Springer International Publishing Switzerland.

Abstract
Recently the RoboCup@Work league emerged in the world's largest robotics competition, intended for competitors wishing to compete in the field of mobile robotics for manipulation tasks in industrial environments. This competition consists of several tasks with one reflected in this work (Basic Navigation Test). This project involves the simulation in Virtual Robot Experimentation Platform (V-REP) of the behavior of a KUKA youBot. The goal is to verify that the robots can navigate in their environment, in a standalone mode, in a robust and secure way. To achieve the proposed objectives, it was necessary to create a program in Lua and test it in simulation. This involved the study of robot kinematics and mechanics, Simultaneous Localization And Mapping (SLAM) and perception from sensors. In this work is introduced an algorithm developed for a KUKA youBot platform to perform the SLAM while reaching for the goal position, which works according to the requirements of this competition BNT. This algorithm also minimizes the errors in the built map and in the path travelled by the robot.

Abstract
This article aims to apply the concepts associated with artificial neural networks (ANN) in the control of an autonomous robot system that is intended to be used in competitions of robots. The robot was tested in several arbitrary paths in order to verify its effectiveness. The results show that the robot performed the tasks with success. Moreover, in the case of arbitrary paths the ANN control outperforms other methodologies, such as fuzzy logic control (FLC).

Abstract
During the last years research and development on legged robots has grown steadily. Leggedsystems present major advantages when compared with “traditional” vehicles, allowinglocomotion in terrain inaccessible to vehicles with wheels and tracks. However, its energy consumption still lag being these vehicles, existing several aspects that need to be improvedand optimized.One of them regards the parameters values that these machines should adopt to minimize the energy consumption. Due to the large number of parameters involved in this optimization process one way to achieve meaningful results is using evolutionary strategies. Genetic Algorithms are away to “imitate nature”replicating the process that nature designed forthe generation and evolutionof species. The objective of this paper is to present a genetic algorithm, running over a simulationapplication oflegged robots, which allows the optimization of several parameters of a quadrupedrobot model, for distinct locomotion gaits. © Springer Science+Business Media Dordrecht 2014.