A Novel Algorithm for Autonomous Robot Navigation System Using Neural Network

Autonomous robot is a type of the robot which can perform operation accurately in any environment. Currently, the demands of robots are increasing in the industry; the autonomous robots suffer from the path planning and obstacle avoidance. To overcome this, many approaches have been proposed but due the noisy environment, it is difficult for the robots to perform navigation. In this work, we proposed an efficient model for the robot navigation using neural networks and to overcome the path planning, kinematics based model is presented. By utilizing the kinematics based stability model, we are able to achieve the stability condition of the robot and it is used for the controlling the speed of the robot. Neural network is used for the obstacle prediction and avoidance. The simulation result presented that the proposed model is robust to noisy (hindrance) environment and it is able to avoid the obstacle precisely at the maximum speed of 0.02 to 1.0 m/s.