Control Strategies for Multi-Robot Systems in Industrial Applications

Abstract

The use of multi-robot systems (MRS) in industrial applications is rapidly transforming manufacturing processes, material handling, and logistics operations. Multi-robot systems offer significant advantages, including increased flexibility, efficiency, and automation. However, controlling multiple robots operating simultaneously requires advanced strategies to ensure cooperation, task allocation, and communication. This paper explores various control strategies employed in multi-robot systems, focusing on their application in industrial environments such as automated assembly lines, warehouse management, and robotic process automation. We discuss centralized and decentralized control approaches, collaborative behavior, and fault tolerance strategies. Additionally, we highlight the challenges of achieving seamless coordination and scalability in large-scale industrial systems. The paper also examines the role of emerging technologies such as artificial intelligence (AI) and machine learning in improving the coordination and efficiency of multi-robot systems.