Advanced Matching Algorithms in Multi-Agent Systems for Industry 5.0

Multi-agent systems are pivotal for Industry 5.0, facilitating the optimization of robotic system coordination to improve production efficiency. Task assignment to robots is accomplished through matching algorithms that consider capabilities and availability, thereby streamlining processes and reducing operational costs. This paper leverages existing research on the coordination of multiple swarms of agents to achieve consensus and adhere to predetermined motion profiles, adapting these findings to the Industry 5.0 context for the control and coordination of diverse robot types. This approach addresses issues of scalability, dynamic environments, and privacy. Experimental results illustrate the efficacy of this approach in optimizing robotic coordination and enhancing production efficiency.