Path following behavior for an autonomous mobile robot using fuzzy logic and neural network

Abstract

In order to achieve tasks by the mobile robots, these robotic systems must have been intelligent and should decide their own action. To guarantee the autonomy and the intelligence for the path following behavior, it is necessary to use the techniques of artificial intelligence like the neural networks and the fuzzy logic. This paper presents an approach for the path following task by an autonomous mobile robot using neural networks and fuzzy logic controllers. The first controller is a Takagi-Sugeno fuzzy model and the second is a multi-layer neural network. The proposed controllers are used for pursing a moving target. The results are compared and discussed.