# An Experimental Framework for 5G Wireless System Integration into Industry 4.0 Applications
## 4 Framework Applicability Example: 5G Autonomous Mobile Robots
### 5G-Connected Autonomous Mobile Robots  
Following the steps of the proposed industrial automation research flow, the 5G-integration of AMRs was done as follows:  
1. An AMR manufacturer would like to start exploring the integration of their products with 5G technology. For mobility reasons, autonomous mobile robots are wireless-native elements. However, as current AMR products operate over Wi-Fi, which presents issues in terms of reliability and scalability when applied to mobile applications [42], optimized alternative are to be explored. AMR vendors are, in general, aware of the techniques for optimizing Wi-Fi performance, however, the products that they sell to their customers will operate over the Wi-Fi networks of the customers, which status remains unknown and might be unoptimized in many cases. Apart from the increased reliability, having 5G-compatible versions of their products would create new business opportunities for AMR vendors. 2. In this case, our industrial partner brought some of their AMR products and related control elements such as the fleet manager (FM) to our lab. The control elements and system architecture were open for us so that we could perform a thorough data traffic analysis of its mode of operation. The targeted AMRs are managed from the centralized FM deployed at infrastructure-side (typically in a server room) and accessible via the Wi-Fi network. From the FM, it is possible to send specific missions with automated paths or set waypoints to navigate to for the AMRs. Although, as wireless-native components, AMRs are based on a wireless-wired hybrid architecture, different from that of the standard static production industrial use cases based only on a wired architecture, the framework can still be applied by identifying the relevant communication interfaces that are subject to be integrated into 5G. In this case, thus interface was the standard AMR communication interface (the same that is used currently in the \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Prototype** & **Processing Delay** & **Jitter** & **Max. Supported Throughput** \\ \hline NTS (v2) & 0.45 ms & 33 μs & N/A \\ \hline
5 GE (v2) & 0.47 ms & 33 μs & N/A \\ \hline WMAGW (v3) L2-tunnel & \textless{}0.4 ms (99.5\%) & 103 μs & 294 Mbit/s \\ WMAGW (v3) IP-mode & N/A & N/A & 480 Mbit/s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Calibrated operational performance specifications of the implemented prototypes. Wi-Fi version of the product), over which the data traffic flowing was analyzed with the help of the NTS device. We observed that control-loops between the AMR and the FM are executed once per second, and they make use of the TCP protocol with average packets sizes of 4 kB and 100 B, in FM-AMR and AMR-FM communication direction, respectively. The total throughput of the AMR application is, therefore, approximately 32 kbit/s (for a single robot). * Based on the throughput, packet sizes and inter-packet times values, it was clear that the current AMR implementation is suitable for operation over 5G and its better mobility and reliability support should result in an improved performance of the AMRs in standard mobility operation conditions than when operated over Wi-Fi. * To integrate the AMR with 5G, a WMAGW (v3) was used. The prototype device was interfaced to the standard communication interface of the AMR by following the 5G-integrated architecture illustrated in Figure 9a. The WMAGW was configured in IP-mode to operate in infrastructure mode to route the control data traffic between the AMR and the FM. In this case, as the architecture of the use case is quite simple, and there are not many communication flows, the IT integration and debugging of the 5G-integrated solution was quite quick. A picture of the deployed 5G-integrated AMR solution is shown in Figure 9b. * To validate the correct operation of the 5G-integrated application, a performance test was carried out. The test was performed by having the AMR automatically navigating within the lab over the measurement route indicated in Figure 9c.