PI controller implementation for the two wheels of a differential robot using NI MyRio

• Autor(a) principal: Oliveira, Ronaldo do Amaral
• Data de Publicação: 2022
• Outros Autores: Cuadros, Marco Antonio de Souza Leite, Valadão, Carlos Torturella
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/28925
• topic: Robótica móvel; Controlador de trajetória; ROS; LabVIEW; AMCL; Ensino de robótica.; Mobile robotics; Trajectory controller; ROS; LabVIEW; AMCL; Robotics teaching.; Robótica móvil; Controlador de trayectoria; ROS; LabVIEW; AMCL; Enseñanza en robótica.

Introduction. This article proposes a navigation architecture for non-holonomic mobile robots for known positions on the navigation map. This architecture can plan a path from the current point to the destination. Navigation is ensured by the move_base controller package of Robot Operating System (ROS) that guides the robot in the predetermined trajectory. Objectives. This article shows the navigation of a non-holonomic robot using (Adaptive Monte Carlo Localization) AMCL algorithm and ROS for educational and development purposes. Methodology. The developed control is compatible with ROS and some examples are shown using a differential robot developed at the Federal Institute of Espirito Santo. The encoders, wheel and robot speed controllers are read in an embedded NI-MyRio system, which is programmed using LabVIEW. ROS is installed on a Linux ODROID minicomputer, which is part of the robot and is connected via Ethernet to a LiDAR laser sensor and to the NI-MyRio. ROS ability to work in a network environment allows control and supervision of devices through computer network. Results. It was possible to perform the navigation of the mobile robot, making it reach the desired final location. Within the experiments, it was possible to prove the functionality of the AMCL algorithm and the proposed architecture. Conclusion. Through the tests performed with the robot, it was possible to conclude that the navigation objective was successfully completed, validating the system and the applicability of the AMCL algorithm.