Abstract
Digital society demands very qualified professionals ready to this environment challenges. This makes necessary to foster the development of competences related to such context such as Computational Thinking or STEAM related skills. However, this is not an easy task, especially because integrating subjects that covers the necessary topics and competences. New active pedagogical approaches are required and this what RoboSTEAM project provides. The application of Challenge Based Learning and Physical Devices and Robotics facilitate the so named twenty first century skills. The project has been developed by several universities and schools and one of most critical parts was testing the methodology and tools, this was done into pilot phases that are described in the present work. The results show that there are important differences between partners socioe-conomical context, but that the outcomes of the project are flexible enough to be applied successfully in any of them.

Abstract
This article presents a comparison between a common type III controller and one based on a brain emotional learning paradigm (BELBIC) parameterized using a particle swarm optimization algorithm (PSO). Both strategies were evaluated regarding the set-point accuracy, disturbances rejection ability and control effort of a DC-DC buck converter. The simulation results suggests that, when compared to the common controller, the BELBIC leads to an increase in both set-point tracking and disturbances rejection ability while reducing the dynamics of the control signal.

Abstract

Abstract
The increase of the world population and a decrease in agricultural labour availability have motivated research robotics in the agricultural field. This paper aims to analyze the state of the art related to manipulators used in the agricultural robotics field. Two pruning and seven harvesting manipulators were reviewed and are analyzed. The pruning manipulators were used in two different scenarios: (i) grapevines and (ii) apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for 5 different products: (i) strawberries, (ii) tomatoes, (iii) apples, (iv) sweet-peppers and (v) iceberg lettuce. The harvesting manipulators showed that a different kinematic configuration is required for different end-effectors, as some end-effectors only require horizontal movements and others require more degrees of freedom to reach and grasp the target. This work will support new developments of novel solutions related to agricultural robotic grasping and manipulation.

Abstract
This paper presents a collaborative mobile manipulator assembly station, which uses force control to surpass the positional uncertainties arising from unstructured work environments and positional errors of the mobile platform. For this purpose, the use case of an internal combustion engine for the automotive industry was considered. Several force control heuristics relying on blind searches using oscillations and/or environment exploration were developed and implemented. Particular attention was given to the orientation errors of the mobile platform, as it was proved that they have a significant impact on the assembly task. The proposed heuristics showed great potential for the use case at hand. Particularly, when the orientation error of the platform is limited to +/- 2 degrees, the oscillation method complemented by environment exploration was able to surpass a maximum translation error of 32.3mm, whereas the environment exploration complemented by orientation correction was able to surpass an error of 73.3mm. Moreover, a generalization strategy was proposed, intending to expand the scope of the developed heuristics to other assembly applications.

Abstract
For remaining competitive in the current industrial manufacturing markets, coating companies need to implement flexible production systems for dealing with mass customization and mass production workflows. The introduction of robotic manipulators capable of mimicking with accuracy the motions executed by highly skilled technicians is an important factor in enabling coating companies to cope with high customization. However, there are some limitations associated with the usage of a fully automated system for coating applications, especially when considering customized products of large dimensions and complex geometry. This paper addresses the development of a collaborative coating cell to increase the flexibility and efficiency of coating processes. The robot trajectory is taught with an intuitive programming by demonstration system, in which an icosahedron marker with multicoloured LEDs is attached to the coating tool for tracking its trajectories using a stereoscopic vision system. For avoiding the construction of fixtures and allowing the operator to freely place products within the coating work cell, a modular 3D perception system was developed, relying on principal component analysis for performing the initial point cloud alignment and on the iterative closest point algorithm for 6 DoF pose estimation. Furthermore, to enable safe and intuitive human-robot collaboration, a non-intrusive zone monitoring safety system was employed to track the position of the operator in the cell.