Abstract
This project arose from the absence in the market of a modular smartphone controlled robot capable of encouraging high school students to program and apply the physics and math's knowledge learned into it. Therefore this project's intention was to study the best way to develop a do-it-yourself (DIY) cost effective robot using only components off the shelf (COTS) and benefit from the omnipresence of smartphones. With the objective of making this robot attractive to anyone with low programming skills, it was important to make it configurable in an easy to understand language and a simple user interface, like the ones provided by Scratch and the MIT AppInventor2. The functional, physical and non-functional requirements for this robot and the free software developed are presented and validated attesting that this project was successfully completed.

Abstract
This article describes an experience in university and high school cooperation. It is expected to foster knowledge and deep learning in secondary schools by turning extra-curricular activities into articulated subject. The robotics area is very useful and generates interest and enthusiasm, even more so when associated with competition. The experience used Lego Ev3 robot and the students learned to program with a healthy technical approach called state machine programming and the easy to use Lego Software programming tool. The participation is enthusiastic because of the participation in the national robotics festival that leads into international RoboCup Federation robotics competitions. The article proposes a set of sessions adequate for secondary school students that constitute the initial step to find a curriculum for robotics in order to simultaneously learn robotics and foster interconnections with the curricular courses in STEM areas, even extending into structured programming issues. The test involved two participations in the national robotics competition that interestingly involved a team of 3 girls and another team of 3 boys although more students were involved during the year that the experience lasted. Declarations from the involved stakeholders are mentioned, even allowing for a brief discussion for women in STEM areas and technology distance for young (wo)men. Some hints, issues and lessons learned are shown. The advocacy of such informal learning strategy is made, advantages and limitations discussed.

Abstract
Robots created for education have different purposes, from learning algorithms to learning robotics. It has been shown that robots can increase the student's interest. Our proposed robot, REDi, uses wire programming to introduce students to the basics of robotics and algorithms. With this robot, attractive, interactive demonstrations can be achieved even with students that have no background in the area.

Abstract
Assessing physical activity (PA) is a challenging task and many different approaches have been proposed. Direct observation (DO) techniques can objectively code both the behavior and the context in which it occurred, however, they have significant limitations such as the cost and burden associated with collecting and processing data. Therefore, this study evaluated the utility of an automated video analysis system (CAM) designed to record and discriminate the intensity of PA using a subject tracking methodology. The relative utility of the CAM system and DO were compared with criterion data from an objective accelerometry-based device (Actigraph GT3X+). Eight 10 year old children (three girls and five boys) wore the GT3X+ during a standard basketball session. PA was analyzed by two observers using the SOPLAY instrument and by the CAM system. The GT3X+ and the CAM were both set up to collect data at 30 Hz while the DO was performed every two minutes, with 10s of observation for each gender. The GT3X+ was processed using cut points by Evanson and the outcome measure was the percentage of time spent in different intensities of PA. The CAM data were processed similarly using the same speed thresholds as were used in establishing the Evenson cut-off points (light: <2 mph; walking: 2-4 mph; very active: >4 mph). Similar outcomes were computed from the SOPLAY default analyses. A chi-square test was used to test differences in the percentage of time at the three intensity zones (light, walking and very active). The Yates' correction was used to prevent overestimation of statistical significance for small data. When compared with GT3X+, the CAM had better results than the SOPLAY. The chi-square test yielded the following pairwise comparisons: CAM versus GT3x+ was chi(2) (5) = 24.18, p < .001; SOPLAY2 versus GT3x+ was chi(2) (5) = 144.44, p < .001; SOPLAY1 versus GT3x+ was chi(2) (5) = 119.55, p < .001. The differences were smaller between CAM and GT3x+, suggesting that the video tracking system provided better agreement than DO. The small sample size precludes a definitive evaluation but the results show that the CAM video system may have promise for automated coding of physical activity behavior.

Abstract
The need for efficient automation methods has prompted the rapid development in the field of Robotics. The development of intelligent robots leads to the ability of them becoming an operator highly efficient and able to adapt to a wide range of problems. Still, despite of the several robotic solutions available, the majority of current industrial robots do not use the Robotic Operative System (ROS) and have limitations in terms of autonomously correct errors during their tasks. An important aspect to consider when developing a new robot is the selection of the methodology for recognition of the objects to be handled. In this paper, it will be presented an approach with enough flexibility to be potentially applicable to different scenarios of object recognition and handling normally found in industrial environment. The main aim is for this application to be applied to pick and place routines in robotics. Moreover it will be presented one particular case study that used the proposed approach, the European Robotics Challenges (EUROC) - a challenge aiming to develop a robot for shop floor logistics and manipulation. Our proposed approach is based on the three tiers paradigm: 1-recognition/sensing tier, 2-effector tier and 3-the control tier and was built using the ROS framework. Since ROS is becoming one of the most useful tools in robotics nowadays, the possibility of using a methodology able to be expressed in ROS allows for the development of a standard approach to pick and place operations. Another advantage of our proposed pick and place approach is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to the insertion of an adaptive control tier in our methodology. The proposed approach can be valuable in the field of robotics and can be potentially applied in multiple tasks and it has already allowed us to advance to the next stage of the already mention challenge.

Abstract
This paper presents a novel localization method for small mobile robots. The proposed technique is especially designed for the Robot@Factory, a new robotic competition which is started in Lisbon in 2011. The real-time localization technique resorts to low-cost infra-red sensors, a map-matching method and an Extended Kalman Filter (EKF) to create a pose tracking system that performs well. The sensor information is continuously updated in time and space according to the expected motion of the robot. Then, the information is incorporated into the map-matching optimization in order to increase the amount of sensor information that is available at each moment. In addition, the Particle Swarm Optimization (PSO) relocates the robot when the map-matching error is high, meaning that the map-matching is unreliable and the robot gets lost. The experiments presented in this paper prove the ability and accuracy of the presented technique to locate small mobile robots for this competition. Extensive results show that the proposed method presents an interesting localization capability for robots equipped with a limited amount of sensors, but also less reliable sensors.