A Networked Multirobot CPS With Artificial Immune Fuzzy Optimization for Distributed Formation Control of Embedded Mobile Robots

Abstract

This article presents a networked multirobot cyber-physical system (CPS) that employs artificial immune fuzzy optimization to achieve distributed formation control of embedded mobile robots. The artificial immune system (AIS) algorithm is combined with a fuzzy system to develop a hybrid optimization technique, called AIS-fuzzy. This metaheuristic is applied to designing the intelligent third cyber and fourth cognition levels in the networked multirobot CPS 5C structure of embedded robots to accomplish distributed formation control. The proposed CPS cyber and cognition levels with AIS-fuzzy paradigm incorporate with the first, second, and fifth levels by means of robotic sensors and actuators. System-on-a-programmable-chip (SoPC) methodology is adopted to present a pragmatic networked multirobot CPS in the field-programmable gate array chips. The presented SoPC-based AIS-fuzzy multirobot CPS features the seamless integration of computation, networking, and physical robotic processes. Experimental results are obtained, and comparative analyses are provided to illustrate the effectiveness and merits of the proposed multirobot CPS to perform distributed formation control of embedded mobile robots.