Proceedings of the 2017 4th International Conference on...

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Proceedings of the 2017 4th International Conference on Advances in Electrical Engineering (ICAEE), 28-30 September, Dhaka, Bangladesh 978-1-5386-0869-2/17/$31.00 ©2017 IEEE An Autonomous Robot: Using ANN to Navigate in a Static path Md. Samiul Haque Sunny 1 , Eklas Hossain 2 , Taskia Nadriba Mimma 1 , Shifat Hossain 1 1 Khulna University of Engineering & Technology (KUET), Khulna-9203, Bangladesh 2 Oregon Tech, Department of Electrical and Renewable Energy, OR-97601, USA E-mail: [email protected] Abstract— A robot with autonomous navigation is not only able to find and follow its exact path but also able to avoid an obstacle which comes in its way without human assistance. This paper deals with an intelligent control of an autonomous robot which is trained with Artificial Neural Network to navigate in a partially structured environment which is full of static obstacles. The training capability according to the sensory input and its response to the obstacles are focused as two main challenges. In this work a Neural Network model is developed. This is done by algorithm of Artificial Intelligence. Then it is trained in Arduino platform for a navigation system designed for autonomous robot. To train the robot, a number of training samples are introduced. Ultrasonic sonar sensors are used with the Neural Network in order to find its route without colliding with any obstacle after the training. This novel approach in robot navigation is expected to open new doors of artificial intelligence in future. Keywords—Autonomous Navigation; Artificial Inteligance (AI); Artificial Neural netowork (ANN); Arduino; Obstacle Avoidance. I. I NTRODUCTION Usually an autonomous robot is a kind of robot that use intelligent algorithms as well as sensors so that it can sense and detect the outside world. The robots which are designed with intelligence have the ability of navigation. This ability can be observed even in dynamic and unknown environment without help of any human being. In many fields such as exploration [2], robotic vehicles [3], home services, industry [1], medical applications [5], surveillance system [4], agriculture and military [6] have applied robots those can move independently especially in outdoors. There are two major steps in an autonomous obstacle avoider robotic navigation system. Firstly, a complex environment with a number of obstacles will be introduced in front of the robot. Among those obstacles some may be dynamic. The robot has to be able to avoid obstacles and also it has to be able to avoid entering a danger zone. These are necessary so that it can complete navigation process Secondly, the robot must possess its own learning capabilities. It is necessary to observe and learn the positions of the obstacles and overcome the collision with the obstacles and navigate in an environment full of dynamic and static obstacles. For example, a robot running on a designated route can face a dynamic obstacle. In that incident, there is a possibility of collision between the robot and the obstacle. In this
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