Obstacle avoidance in mobile robot using Neural Network

Abstract

Investigate mobile robot's history, obstacle avoidance is one of most important research area and also the foundation of building robot's successful behaviors. This paper proposes a Neural Network control system that is able to guide the mobile robots (AmigoBot and P3DX) traverse through a maze with arbitrary obstacles. The pattern is trained by using Matlab toolbox and Aria library for motion control. There are 256 specific patterns defined to help robot organize the situation. For input data, sonar and laser range finder are two main sensors for passing on information of environment. The empirical results show the effectiveness and the validity of the obstacle avoidance behavior of Neural Network control strategy.