The basics of the identification, localization and navigation for mobile robots

This article is an implementation of the results described in earlier papers for odometry modelling and navigation system synthesis. It'll be part of the introduction in Erasmus+ Innovative Open Education on IoT. It's already used for MOOC course published on national education platform https://openedu.ru/, the e-learning control theory course used in ITMO University. The main goal of this course to give to the students an idea of the connection formulas, models and physical objects. The course consists from the DC-motor parameters identification, engine model description, linear and nonlinear controllers implementation, encoders and IMU-sensors odometry motion model. This experience was used for a formulation the navigation problem with the NXT differential drive mobile robot. Based on the method proposed in [1] the robot to goal movement with the obstacle avoidance task was solved. It presents a simple and demonstrative example for choosing a Lyapunov function candidate for controller design for a nonlinear system based on the robot-goal distance and the orientation error regarding the goal position.