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

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.