Implementation of a position and movement controller for a differential mobile robot

Context: Mobile robotics remains being an area of constant updating, which seeks to have applications to improve the life quality of human beings. Therefore, the paper presented a novel design of a position and move controller to a differential mobile robot using artificial neural networks, which aims is to bring a real applications in different fields. Method: The proposal is based on a PID controller, which has been tuned using a neural network and requires knowledge of the kinematic model of the robot. Results: The simulations show the efficiency of the control position for following paths, in this case for tracking straight and curved paths. The graphical interface allows adjusting the gains easily and verifies the trajectory tracking online. Conclusions: From the results we can conclude that the proposed strategy is easy to implement since the required information is generally deliver by mobile robot sensors. Finally, tuning PID controller with the neural network allows obtaining a correct performance for trajectory tracking