# Prototype of 5G Integrated with TSN for Edge-Controlled Mobile Robotics
## 1 Introduction  
A large-scale communication network is a crucial aspect of smart factories. It not only enables communication among actuators and sensors, enabling an adaptive and flexible process, but also an integration of large computing resources such as edge cloud and factory cloud systems. Factory cloud refers to a local server system near the shopfloor with cloud capabilities. Artificial intelligence, big data analysis, and cloud-based control systems increase production efficiency and quality by enabling overall orchestration and optimization. Combined with wireless communication, the digitalization of production systems can achieve high flexibility, allowing customized products with a batch size of one. Especially autonomous guided vehicles and mobile robots can benefit from wireless communication and cloud systems. Moving path planning and control algorithms to a factory cloud system enables smart and collaborative decision making and fast reaction without efficiency loss. Industrial manufacturing communication needs to meet rigorous requirements regarding reliability, availability, and real-time capability [1, 2]. State-of-the-art real-time communication is dominated by fieldbus protocols, such as EtherCat, PROFINET/PROFIBUS, or CC-Link. These protocols were designed for local connections inside a machine or a production cell with the focus on the high reliability and short cycle times. As a result, they are mostly manufacturer-specific and at the most compatible on the physical layer. Furthermore, all these solutions for industrial communication are wired based, creating static connections. Wireless solutions have only been used for a limited numberof applications in industry, which are caused by the high requirements in the production environment [3; 4]. Current state-of-the-art solutions such as Wi-Fi or Bluetooth cannot serve these requirements; therefore, communication networks are limited to wired communication. In consequence, industrial networks are rigid and do not provide the flexibility and connectivity needed for Industry 4.0. Two main deficits have been identified: Existing communication solutions are vendor specific and therefore not compatible with each other, and they do support wireless solutions. With IEEE 802.1 Time-Sensitive Networking (TSN) [5], a set of standards for deterministic communication has been introduced to IEEE 802.1 and IEEE 802.3 to support real-time communication over Ethernet networks. With TSN, large-scale Ethernet networks can transmit real-time critical data suitable for industrial applications [6; 7]. This reduces the need for specific fieldbus protocols and vendor-specific communication systems. TSN introduces three main areas to Ethernet: time synchronization, sending scheduled traffic, and centralized, automated system configuration [8]. In the prototype, TSN is used for the wired connection of the field devices with the factory cloud. Owing to its compatibility with enterprise networks, its vendor independence, and its scalability, TSN is well suited for large-scale networks for production in future. The 5G system is seen as a key enabling technology for wireless communication in industrial use cases. Meanwhile, 3 GPP, the standardization body for 5G, has made design considerations from the very beginning to define technology features that allow ultra-reliable low-latency communication (URLLC) for industrial use cases [9; 10]. The 3 GPP Releases 15 and 16 specify various technology features to enhance reliability and provide low-latency communication, including faster signaling schemes, traffic prioritization, redundancy and robustness for control and data transmission, etc. [11]. Furthermore, 3 GPP has specified the technological framework to allow the integration of 5G with TSN [12; 13; 14]. The basic functionalities and features to allow 5G integration with TSN have been completed in 3 GPP Releases 16 and 17. The 5G system is treated as a TSN bridge in the 5G-TSN integration framework.