Mejoramiento de la postura estimada en un robot móvil mediante el Filtro Kalman Unscented.

This article presents the implementation of the Unscented Kalman Filter (UKF) to improve the estimation of the pose of a differential mobile robot. The algorithm was validated and implemented using real robot data in MATLAB and Python, as well as its simulation in Gazebo-ROS. The results showed that the filter improved the estimation of the robot's state and performed well in all tests conducted. Additionally, the advantages of the UKF compared to other filters were discussed. The article also presented a control method for a differential robot that uses a PID on each wheel to follow a desired trajectory. It was concluded that the implementation of the UKF filter improved the estimation of the robot's pose. [Extracted from the article]