Neural network simulation for obstacle avoidance and wall follower robot as a helping tool for teaching-learning process in classroom

Abstract

One of the most applied technologies is robotics, and one the most applied type of robots is a mobile robot. To provide a tool for the interactive teaching-learning process in the classroom, a simulation program is needed. Low price and easy to use software is preferable considering not every polytechnic can provide expensive simulation software for its students. Robotics related curriculum should include artificial intelligence since it is functioning as a brain to the robot. One type of artificial intelligences is neural networks. This study presents the application of neural networks by using low price simulation software. The simulation results show the feasibility of utilizing the software for the students to learn neural networks by variating the scenarios of mobile robots application, adding more robots, more sensors and writing the programs to control the robots. The contribution of this paper is to show and inspire teachers to create a more interactive teaching-learning process in the classroom by using low price, user-friendly software, and to encourage them to search more alternatives of low price or even free software to be the teaching tool in the classroom.