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
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.

Abstract
Micromouse is one of the most popular competitions among mobile robotics researchers. This competition brings together several challenges in the field of mobile robotics. It represents an excellent tool in competition field since it stimulates the development and multidisciplinary knowledge as well as group cooperation to carry out the best approach. This work presents a contribution to this issue on exploring the unknown environment and the robot location to obtain an optimized trajectory in the maze, using the modified Floodfill algorithm that considers the cost for the robot rotations around its axis. A comparison is conducted between the modified algorithm and the traditional Floodfill procedure.

Abstract
There is an increasing number of mobile robot applications. The demanding of the Industry 4.0 pushes the robotic areas in the direction of the decision. The autonomous robots should actually decide the path according to the dynamic environment. In some cases, time requirements must also be attended and require fast path planning methods. This paper addresses a comparison between well-known path planning methods using a realistic simulator that handles the dynamic properties of robot models including sensors. The methodology is implemented in SimTwo that allows to compare the A* and RRT* algorithms in different scenarios with dynamic and real time constraint scenarios. Copyright

Abstract
The micromouse competition has been gaining prominence in the robotic atmosphere, due to the challenging and multidisciplinary characteristics provided by the teams' duels, being a gateway for those who intend to deepen their studies in autonomous robotics. In this context, this paper presents a realistic micromouse simulator developed with Unity software, a widely game engine with dynamics and 3D development platform used. The developed simulator has hardware-in-the-loop capabilities, aims to be simple to use, it can be customizable, and designed to be as similar as possible to the real robot configurations. In this way, the proposed simulator requires few modifications to port the microcontroller code to a real robot. Therefore, the framework presented in this work allows the user to simulate the development of new algorithm strategies dedicated to competition and also hardware updates. The simulation supports several mazes, from previous competitions and has the possibility to add different mazes elaborated by the user. Thus, the features and functionality of the simulator can serve to accelerate the project's development of the beginning and advanced competitors, using real models to reduce the gap between the mouse robot behavior in the simulation and the reality. The developed simulation environment is available to the community.

Abstract
Robotics in education has special relevance in current digital society where students should know how to deal with technology. In this paper, it is presented an educational experiment in the mobile robotics domain. The referred experiment was part of a summer camp, which took place at the Polytechnic Institute of Bragança Portugal, being its technological aspects related with mobile robotics. Other than the technological aspects, the students participated in many different cultural and social activities, having the opportunity to know the city of Bragança and also to know different persons, mainly students, professors, researchers and laboratory technicians. The applied approach in the summer camp was a challenge based learning methodology, being involved in the experiment 3 professors, 4 monitors, working with a group of 16 secondary school students. The described experiment was planned as an activity of the RoboSTEAM - Integrating STEAM and Computational Thinking development by using robotics and physical devices ERASMUS+ Project. © 2019 ACM.