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- An openmodelica package for BELBICPublication . Coelho, João Paulo; Coelho, J. A. B.; Braz-César, ManuelThis paper presents the development and implementation of a new package for OpenModelica that integrates the Brain Emotional Learning Based Intelligent Controller (BELBIC) approach into control system simulations. BELBIC, inspired by neurobiological models of emotional learning, has demonstrated effectiveness in handling complex, nonlinear, and adaptive control problems. The proposed package provides a modular and user-friendly framework for integrating BELBIC enabling researchers and engineers to design, simulate, and analyze intelligent control strategies within an open-source environment. Key features of the package include customizable emotional response parameters and compatibility with existing Modelica libraries. To validate the package, a set of examples are included which demonstrates its application to the control of common dynamic systems.
- Modeling and control of an educational manipulator robot jointPublication . Coelho, J. A. B.; Brancalião, Laiany Suganuma; Alvarez, Mariano José; Costa, Paulo; Gonçalves, JoséIntegrating physical robots in an educational context often entails acquiring Expensive equipment that often operates using proprietary software. Both conditions restrict the students from exploring and fully understanding the internal operation of robots. In response to these limitations, a three-degree-of-freedom robotic manipulator, based on the “EEZYbotARM MK2” open-source design by Carlo Franciscone, is being repurposed and integrated within the SimTwo simulation environment to operate within a hardware-in-the-loop architecture. To accomplish this objective, first, an open-source Arduino-based library was developed aiming at the robot’s online and offline programming akin to industrial robots. The firmware is able to communicate with the SimTwo software in which the digital twin’s robot is living. The dynamic behavior of the robot’s digital twin must be properly parametrized and aligned with the physical robot’s dynamics. This article describes the modeling of the robot joint’s actuator and its closed-loop controller formulation. The obtained results show that the dynamic behavior of the robot joint digital twin closely matches both open and closed-loop, the one of its physical counterpart.
- Integrating SolidWorks, LabVIEW, and Arduino in Robotics EducationPublication . Coelho, João Paulo; Coelho, J. A. B.; Gonçalves, JoséThis paper explores the integration of SolidWorks, LabVIEW, and Arduino as a comprehensive and cost-effective approach to teaching robotics to undergraduate students. In scenarios where real hardware is unavailable or prohibitively expensive, this methodology offers significant advantages. SolidWorks enables students to design and simulate robotic components in a virtual environment, fostering a deep understanding of mechanical design and engineering principles. LabVIEW provides an intuitive graphical interface for programming and control, allowing students to develop and test their algorithms. Finally, Arduino, as an open-source hardware platform, bridges the gap between virtual simulations and physical implementation, offering a hands-on experience with minimal financial investment. Together, these tools create a robust educational framework that enhances theoretical knowledge through practical application, encourages innovation, and prepares students for real-world engineering challenges. The paper concludes that this integrated approach not only mitigates the limitations of resource constraints but also enriches the learning experience by providing a versatile and accessible platform for robotics education.
- Realistic simulation for dataset generation in a mobile robotics educational contextPublication . Brancalião, Laiany Suganuma; Alvarez, Mariano José; Coelho, J. A. B.; Conde, Miguel Ángel; Costa, Paulo; Gonçalves, JoséIn 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.