Teaching Control Theory using Mobile Robot Obstacle Following/Avoidance with CoppeliaSim and MFO Algorithm. - Pastrana, M. A.; Bautista, J.; Mendoza-Peñaloza, Jose; Oliveira, L. H.; Mendes, D. A.; Muñoz, Daniel M. (Anais do Simpósio Brasileiro de Robótica e Simpósio Latino Americano de Robótica (SBR/LARS); 2023: Anais do XV Simpósio Brasileiro de Robótica e XX Simpósio Latino Americano de Robótica, 2023)
The advancements in information and communication technologies have had a significant impact on the engineering educational system. Virtual laboratories are progressively being adopted to improve the way in which students interact with simulations for control systems. The enhancement of visualization and interaction offered by modern computers presents an opportunity to teach the theoretical foundation with a more organic approach. In addition, there are optimization algorithms that can be employed to designing controllers in an optimal way without having extensive knowledge in the area of control theory. This paper delineates the utilization of CoppeliaSim software, the Moth Flame Optimization (MFO) algorithm, and the EVA mobile robot for teaching control theory with Single-Input, Single-Output systems (SISO), for mobile robot obstacle following/avoidance application. The approach employs an online multi-language (Spanish and Portuguese) methodology for students without knowledge of control theory.