Intelligent neuro-controller for navigation of mobile robot

Abstract

This paper deals with the reactive control of an autonomous robot which move safely in a crowded real world unknown environment and to reach specified target by avoiding static as well as dynamic obstacle. The inputs to the proposed neurocontroller consist of left, right, and front obstacle distance to its locations and target angle between a robot and a specified target being acquired by an array of sensors. A four layer neural networks is used to design and develop the neurocontroller to solve the path and time optimization problem of mobile robots which deals the with cognitive tasks such as learning, adaptation, generalization and optimization. Back propagation method is used to trained the network. This paper analyzes the kinematical modeling of mobile robots as well as the design of control systems for the autonomous motion of the robot. The training of the nets and the control performances analysis have been done in a real experimental setup. The simulation results are compared with experimental results which are satisfactory and shows a very good agreement.