Abstract
Since creating universally capable robots is challenging for a single manufacturer, a diverse fleet of robots from various manufacturers is utilized. However, these heterogeneous fleets encounter communication and interoperability issues. As a result, there is a growing need for a standardized interface that is capable of communicating, controlling and managing a diverse fleet without these interoperability issues. This paper presents a translation software module capable of controlling an autonomous mobile robot and communicating with a ROS-based robot fleet manager using the VDA5050 Standard and exchanging information via the MQTT communication protocol, aiming at flexibility and control across different robot brands. The effectiveness of the software in controlling a mobile robot via the VDA5050 standard was demonstrated by the results. It accurately analysed data from the Robot Fleet Manager, converted it into VDA 5050 JSON messages and skilfully translated it back into ROS messages. The robot's behavior remained consistent before and after the VDA5050 implementation.

Abstract
Autonomous Mobile Robots (AMR) are seeing an increased introduction in distinct areas of daily life. Recently, their use has expanded to intralogistics, where forklift type AMR are applied in many situations handling pallets and loading/unloading them into trucks. One of the these vehicles requirements, is that they are able to correctly identify the location and status of pallets, so that the forklifts AMR can insert the forks in the right place. Recently, some commercial sensors have appeared in the market for this purpose. Given these considerations, this paper presents a comparison of the performance of two different approaches for pallet detection: using a commercial off-the-shelf (COTS) sensor and a custom developed application based on Artificial Intelligence algorithms applied to an RGB-D camera, where both the RGB and depth data are used to estimate the position of the pallet pockets.

Abstract
This article presents the prototyping of an educational manipulator robot, based on the EEZYbotARM Mk2 robot, tailored for first-year master's students in the field of robotics. The project encompasses the assembly of the robot arm, computation of both forward and inverse kinematics, and analysis of two path-planning movement algorithms. These features are consolidated into an Arduino library to streamline the process for students to generate instructions for the robot. The EEZYbotARM Mk2 features a three-degree-of-freedom revolute arm with a gripper that remains parallel to its base at all times, enhancing its suitability for educational applications such as pick-and-place tasks. The article provides detailed descriptions of the materials and methods employed, along with proposed challenges for student engagement.

Abstract
In this paper it is presented a Hardware-in-theloop (HIL) mobile robot programming approach, to be applied in a robotics educational context. The motivation to apply this approach is the fact that students can program the robots without access to the robot hardware, but still maintain some important closed loop control critical features, such as a realistic lag time and the possibility for a larger number of students to program at the same time. Therefore, the developed software is applied to the real hardware without any change. The HIL approach was applied to provide a simulation close to reality, once the processing occurs in the real robot processor and the actuation and sensorization inside the simulation, adding to the advantage to test the firmware avoiding damage in the physical robot.

Abstract
Our contemporary society necessitates professionals equipped with 21st-century skills. Disciplines within Science, Technology, Engineering, Arts, and Mathematics (known as STEAM) have been particularly effective in fostering these skills. However, when considering students with disabilities, especially those with intellectual or developmental disabilities (IDD), this assertion often falls short. In this context, the RoboSTEAMSEN project emerges as an initiative designed to enhance educational processes by providing teachers of IDD students with the necessary resources to promote STEAM engagement. The project proposes the use of active learning methodologies and robotics to achieve this goal. The primary objective of the project is realized through several strategies: understanding the needs of students with disabilities and adapting the use of robotics and active learning methodologies accordingly; training teachers in the use of these resources; and creating a platform to exchange experiences, resources, lessons learned, tools, case scenarios, etc., while reaching other potential stakeholders such as caregivers and policymakers. The main outcomes of the project are teacher training programs and the development of associated competencies, tools to identify and classify resources for the students, and technological platforms to ensure the sustainability of the project once it concludes.

Abstract