Estimação de estado usando fusão de sensores para um robô holonômico

Abstract

With the arrival of Fourth Industrial Revolution, robotics has become a more popular anddesiredmarket. Articulatedrobots,automaticallyguidedvehicles(AGV),humanoids, autonomous mobile robots (AMR), and others; have been the subject of large studies with the aim of carrying out repetitive, complicated work or work that would endanger human life. In mobile robotics, whose objective is to allow the robot to move around in a work environment, challenges arise in the field of navigation. This work presents a modeling for the position tracking problem for mobile robots using sensor fusion, proprioceptive and exteroceptive sensors, through the Kalman filter. The modeling uses an inertial measurement unit (IMU) and a camera as sensors, both of low cost, to carry out the filter processes, and its implementation is done using ROS, aiming at integration in any device that is compatible.