Abstract
Localization is essential to modern autonomous robots in order to enable effective completion of complex tasks over possibly large distances in low structured environments. In this paper, a Extended Kalman Filter is used in order to implement self-localization. This is done by merging odometry and localization information, when available. The used landmarks are colored poles that can be recognized while the robot moves around performing normal tasks. This paper models measurements with very different characteristics in distance and angle to markers and shows results of the self-localization method. Results of simulations and real robot tests are shown.

Abstract

Abstract
This paper describes the 5dpo-2000 team, The paper will be divided into three main sections, corresponding to three main blocks: the Global Level, the Local Level and the Interface Level. These Levels, their subsystems and some implementation details will be described next.

Abstract
Fuzzy Logic is a part of Artificial Intelligence science and provides for control of complex processes, where exact models are not applicable. Such a controller is necessary for the process of drying oil filled transformers. Indeed, this controller needs to tackle with a highly non-linear and time variant process. The development of the controller was fast and the implementation size very small. Its performance proved very robust whilst providing both good dynamical and steady-state behaviour.

Abstract
The goal of the "Soft Core Robot" project is to set the way for a robot with minimalistic component and pin count, based on custom computing. Additionally, the "Joint Wheel Motion Controller" specifically takes advantage of custom computing in order to privilege angular precision over linear velocity which is interesting for some applications including mobile robotics. The proposed "Soft Core Robot" is expected to produce a small but very powerful and versatile robot. The chosen processing platform is based on a FPGA plus Microprocessor in the same chip. The proposed example application is the Fire Fighting contest at Instituto Politecnico da Guarda, in Portugal. The Joint Wheel Controller is not yet fully operational but results for the control of a single motor are presented. The overall status of the project is addressed, as well as the pros and cons of the approaches taken.

Abstract
Recent years have brought an increasing interest on analyzing efficiently the performance of sports players during training sessions and games. The information collected from such analysis is very valuable to educators and coaches since it allows them to better understand the difficulties of a trainee, a player or even an entire team and formulate adequate training and strategic plans accordingly. In order to perform this analysis in a consistent and systematic way, sophisticated sensory systems and data processing techniques are needed. This paper presents a survey on relevant work, current techniques and trends on the area of team tracking systems applied to sports. We propose a classification of these systems by distinguishing them into two main categories: intrusive and nonintrusive. Nonintrusive systems are further refined into outdoor and indoor sports applications. The specific characteristics of each system are itemized, including the identification of the strong points and limitations. Finally, the paper highlights some open issues and research opportunities on this area. © 2010 IEEE.