Conflict‐Free Planning and Data‐Driven Control of Large‐Scale Nonlinear Multi‐Robot Systems

Abstract

ABSTRACT This paper addresses a crucial challenge in the domain of smart factories and intelligent warehouse logistics, focusing on conflict‐free planning and the smooth operation of large‐scale nonlinear mobile robots. To tackle the challenges associated with scheduling large‐scale mobile robots, an improved space–time multi‐robot planning algorithm is proposed. The cloud servers are adopted in this algorithm for computation, which enables faster response to the planning requirements of large‐scale mobile robots. Furthermore, enhancements to a model‐free adaptive predictive control method are proposed to enhance the networked control effectiveness of the nonlinear robots. The algorithm's capability to accommodate conflict‐free path planning for large‐scale mobile robots is demonstrated through simulation results. Experimental findings further validate the effectiveness of the cloud‐based large‐scale mobile robot planning and control system in achieving both conflict‐free path planning and accurate path tracking. This research holds substantial implications for enhancing logistics transportation efficiency and driving advancements in the field of smart factories and intelligent warehouse logistics.