Novel Development of Fuzzy Controller Based Multi-Agent System for Efficient Navigation of Autonomous Robots

Author:

Emil Selvan G. S. R.1,Jagadeesh Kannan R.2,Sangapu Sreenivasa Chakravarthi3,Shalini S.4,Pandurangan Raji5,Raj E. Fantin Irudaya6

Affiliation:

1. Department of Computer Science and Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu, India

2. School of Computer Science & Engineering, Vellore Institute of Technology Chennai Campus, Vandalur Kelambakkam Road, Chennai, Tamilnadu, India

3. Department of CSE, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Chennai, India

4. Department of Mathematics, J.N.N Institute of Engineering, Kannigaipair, Chennai, Tamilnadu, India

5. Saveetha Engineering College, Thandalam, Chennai, Tamilnadu, India

6. Department of Electrical and Electronics Engineering, Dr. Sivanthi Aditanar College of Engineering, Tiruchendur, Tamilnadu, India

Abstract

This study investigates a fuzzy controller technique for autonomous robot navigation in both the static and dynamic environmental conditions and an excessive number of pathways to the destination. The design and implementation of a novel obstacle avoidance technique for autonomous robots are developed using the fuzzy controller-based multi-agent system. This method allows the Robot to identify dynamic or static unidentified objects while directing the Robot to prevent collisions and advance toward the objective. The Robot is capable of moving in a variety of environments. The Robot may communicate and travel in dynamic space by perceiving its surroundings and pursuing a free-collision route. This study covers creating a multi-agent system that includes fuzzy logic to regulate the robotic movements along a path reactive for effective Navigation. This project aims to develop an algorithm that allows the Robot to do distinct tasks to accomplish a unified objective, autonomous Navigation in a slightly unfamiliar environment. Under such a situation, the usage of a multi-agent system is advantageous. As a result, we created a framework made up of four agents responsible for sensing, Navigation, dynamic, and static obstacle avoidance. These agents communicate with one another via a coordinating mechanism.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

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