Abstract
STEAM Education is nowadays a key element for our current digital society. Integrating STEAM and developing competences such as Computational Thinking is highly demanded by the industry and higher education institutions. In order to do so new methodological approaches are required. RoboSTEAM project is an Erasmus+ project defined to address these topics by using of physical devices and robotics employing Challenge Based Learning methodology. One of the first steps in the project development is the definition of current landscape in the research field. Which means to carry out a literature mapping that considers previous applications of Challenge Based Learning in STEAM education and use of robots and physical devices to do so. This paper shows the mapping review process and the main results obtained. The mapping analyze 242 candidate works from the most relevant bibliographic sources and selected 54. Form them it was possible to see that there are not many initiatives on STEM Education related to Challenge base learning and the most of them are specially focused on the application of specific tools and in the development of concrete competences.

Abstract
Rehabilitation is an important recovery process from dysfunctions that improves the patient's activities of daily living. On the other hand, collaborative robotic applications, where humans and machines can share the same space, are increasing once it allows splitting a task between the accuracy of a robot and the ability and flexibility of a human. This paper describes an innovative approach that uses a collaborative robot to support the rehabilitation of the upper limb of patients, complemented by an intelligent system that learns and adapts its behaviour according to the patient's performance during the therapy. This intelligent system implements the reinforcement learning algorithm, which makes the system robust and independent of the path of motion. The validation of the proposed approach uses a UR3 collaborative robot training in a real environment. The main control is the resistance force that the robot is able to do against the movement performed by the human arm.

Abstract
Realizing autonomous inspection, such as that of power distribution lines, through unmanned aerial vehicle (UAV) systems is a key research domain in robotics. In particular, the use of autonomous and semi-autonomous vehicles to execute the tasks of an inspection process can enhance the efficacy and safety of the operation; however, many technical problems, such as those pertaining to the precise positioning and path following of the vehicles, robust obstacle detection, and intelligent control, must be addressed. In this study, an innovative architecture involving an unmanned aircraft vehicle (UAV) and an unmanned ground vehicle (UGV) was examined for detailed inspections of power lines. In the proposed strategy, each vehicle provides its position information to the other, which ensures a safe inspection process. The results of real-world experiments indicate a satisfactory performance, thereby demonstrating the feasibility of the proposed approach.

Abstract
In this paper it is described a Pilot that took place at Emidio Garcia School from Braganca, Portugal. The presented Pilot is based on a Challenge based Learning Approach, being an activity of the RoboSTEAM - Integrating STEAM and Computational Thinking development by using robotics and physical devices - ERASMUS+ Project. In the presented educational experiment it were used physical devices, being chosen the mBot robot, programmed using Scratch. The presented challenges had as research question a global problem that was Wildfires. Student had to propose and to develop solutions based on the use of robots to prevent and fight wildfires. The students that participated in the experiment were secondary school students, from Spain and Portugal, with their background in technology and arts respectively. Previously to the experiment the involved students filled a STEM semantic Survey and during the experiments their performance was evaluated.

Abstract
Nowadays, companies are demanding better-prepared professionals to succeed in a digital society, and the acquisition of Science, Technology, Engineering, Arts, and Mathematics (STEAM)-related competencies is a key issue. One of the main problems in this sense is how to integrate STEAM into the current educational curricula. This is not something related to a subject or educational trend but rather to new methodological approaches that can engage students. In this sense, such active methodologies that apply mechatronics and robotics could be an interesting path to pursue. Given this context, the first necessary task in evaluating the potential of this approach is to understand the landscape of the application of robotics and mechatronics in STEAM Education and how active methodologies are applied in this sense. To carry out this analysis in a systematic and replicable manner, it is necessary to follow a methodology. In this case, the researchers employ a systematic mapping review. This paper presents this process and its main findings. Fifty-four studies have been selected out of 242 total studies analyzed. From these, beyond obtaining a clear vision of the STEAM landscape regarding project topics, we can also conclude that robotics and physical devices have been applied successfully with collaborative methodologies in STEAM Education. Regarding conclusions, this paper shows that robotics and mechatronics applied with active methodologies is to be a good means to engage students in STEAM disciplines and thus aid the acquisition of what is commonly known as "21st-century skills."

Abstract
The use of robots to map disaster-stricken environments can prevent rescuers from being harmed when exploring an unknown space. In addition, mapping a multi-robot environment can help these teams plan their actions with prior knowledge. The present work proposes the use of multiple unmanned aerial vehicles (UAVs) in the construction of a topological map inspired by the way that bees build their hives. A UAV can map a honeycomb only if it is adjacent to a known one. Different metrics to choose the honeycomb to be explored were applied. At the same time, as UAVs scan honeycomb adjacencies, RGB-D and thermal sensors capture other data types, and then generate a 3D view of the space and images of spaces where there may be fire spots, respectively. Simulations in different environments showed that the choice of metric and variation in the number of UAVs influence the number of performed displacements in the environment, consequently affecting exploration time and energy use.