Smart Navigation of Mobile Robot Using Neural Network Controller
Khaled Khnissi, Chiraz Ben Jabeur Seddik, Hassene Seddik · 2018
The field of autonomous navigation of mobile robot is advancing so fast especially with the development of machine learning algorithms. This study aims to introduce a neural network controller that controls the trajectory and the obstacle avoidance of a non-holonomic mobile robot.We train the robot in environment containing multiple obstacles with different places. This paper includes both a kinematic and a dynamic study of a mobile robot. Different training schemes have been studied that tackle the learning objectives differently. The trained controller is producing the Pulse Width Modulation (PWM) signals that could be implemented in a microprocessor and validated by simulations. Unlike some other recent approaches, this work was validated by a 3D simulation which is similar to the real model.