RoboPlan5G: Coordinating Cloud-Controlled Mobile Robots with 5G Network Configuration - Jorgensen, Nils; Kattepur, Ajay; Mohalik, Swarup; Vulgarakis, Aneta; Fersman, Elena (Proceedings (IEEE International Conference on Emerging Technologies and Factory Automation), 2023)
With the emergence of Industry 4.0, comes an increasing need for multi-robot coordination and communication to efficiently complete joint tasks. A critical technology is the fifth generation (5G) mobile network, which enables cloud-controlled robots to execute tasks with differentiated quality-of-service (QoS) features. While there has been significant research on multi-robot planning, the integration with the capabilities of realistic network systems has been limited. In this paper, we introduce RoboPlan5G, a framework for 5G-aware robot planning. We propose a joint state-search model that includes task planning coordination in conjunction with 5G physical resource block (PRB) allocation. This process ensures efficient usage of the limited indoor 5G spectrum and effective service performance, while still aiming for the completion of tasks in the shortest possible time frame. Scenarios are generated in an Industry 4.0 environment, where the planner is shown to decrease the required 5G spectrum allocation by 50%, and on average improve the plan quality by 45% while maintaining a small computation time.