Fuzzy-based Navigation and Control of a Non-Holonomic Mobile Robot

TL;DR

This paper develops a fuzzy logic controller for a non-holonomic mobile robot, demonstrating its effectiveness through simulations and comparing different membership function sets.

Contribution

It introduces a fuzzy logic control model tailored for autonomous mobile robots and evaluates its performance with various membership functions.

Findings

Fuzzy logic controller with three input memberships outperforms those with five and seven.

Simulation results validate the proposed fuzzy control approach.

The model enhances the navigation capabilities of non-holonomic robots.

Abstract

In recent years, the use of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, a theoretical model of a fuzzy based controller for an autonomous mobile robot is developed. The paper begins with the mathematical model of the robot that involves the kinematic model. Then, the fuzzy logic controller is developed and discussed in detail. The proposed method is successfully tested in simulations, and it compares the effectiveness of three different set of membership of functions. It is shown that fuzzy logic controller with input membership of three provides better performance compared with five and seven membership functions.