José Alexandre Gonçalves

Abstract
In the context of mobile robotics education, realistic and accessible datasets are fundamental for supporting the development and testing of algorithms. However, collecting real-world data is a limited and challenging task because it is time-consuming and error-prone. Therefore, this paper presents the generation of a synthetic dataset through realistic simulation using the SimTwo environment-a physics-based simulator, and modeling techniques of sensors and actuators. The physical and simulated mobile robot was developed to perform tasks such as following a line, following a wall, and avoiding obstacles. The proposed approach facilitates the creation of customized datasets for training and evaluation algorithms while supporting remote and inclusive learning. Results show that a simulated dataset can effectively replicate real-world behaviors, making them a valuable resource for educational contexts, research, and development. Some emergent machine learning algorithms can be applied to this dataset, being this approach increasingly used to enhance robot localization, by leveraging ML, robots can improve the accuracy, robustness, and adaptability of their localization systems, especially in complex and dynamic environments.

Abstract
The integration of students with intellectual and developmental disabilities into STEAM education presents ongoing challenges, particularly in engineering disciplines where both technical and social competencies are essential. Robotics and active learning methodologies have emerged as promising solutions to address these challenges by offering adaptive, interactive, and student-centered learning environments. This study conducts a systematic literature review to examine how these technologies and methodologies are applied to support students with Intellectual and Developmental Disabilities. A total of 34 high-quality studies published over the past ten years were selected through a rigorous process of database searching, inclusion/exclusion filtering, and quality assessment. The analysis reveals that robotics is particularly effective in fostering academic development, cognitive skills, social-behavioral interaction, and emotional regulation, while active learning promotes social responding, role understanding, and collaborative skills. Together, these approaches not only enhance individual learning outcomes but also facilitate the broader inclusion of students with disabilities within engineering education.

Abstract
This paper presents the development of an automated water sampling system designed to enhance quality control in water treatment facilities. The system is built around a mechanical structure that houses a watertight box containing all electronic components. A display inside the box allows users to program sampling schedules, including parameters such as the day, time, number of samples, sample volume, and intervals between samples. A balance integrated into the structure holds a bottle that collects the water samples, while a reservoir at the bottom accumulates water to ensure an adequate supply. A water pump connected to the structure enables controlled sample collection. The design ensures that all components are compactly integrated, while a non-invasive method is used to measure the volume of the sampled water, thereby avoiding direct contact between the sensors and the sample. A Project-Based Learning (PBL) approach, coupled with direct industry collaboration, has reinforced the effectiveness of active learning methodologies in engineering education.

Abstract
This paper explores an innovative distributed real-time control system for a 3D-printed robotic leg. The system is constructed on a modular multi-board architecture that seamlessly integrates with ROS2 and micro-ROS, demonstrating the use of 3D printing for rapid prototyping and customized solutions. A notable feature of this robotic leg is its 360-degree rotating joint, which extends its range of motion, enabling intricate and versatile movements. Incorporating a shoulder joint further facilitates sideways mobility, augmenting its operational capabilities. A multi-board architecture is designed to ensure efficient communication, ease of component interchangeability, and robust scalability for future development. Additionally, advanced control techniques, including tuning of proportional-integral-derivative (PID) controllers, ensure responsive joint actuation tailored to the unique properties of 3D-printed materials. Experimental validation indicates low latency and stable operation, underscoring the system's effectiveness for real-time robotic applications.

Abstract