Evaluation of combined network slicing and MEC towards mobile robot applications in 5G networks

Abstract

[EN] Wireless communications have been used widely for monitoring purposes in different applications such as smart metering, environmental sensing, industrial asset tracking or healthcare monitoring. However, the enhancement of wireless technologies such as Wi-Fi and 5G NR provides new opportunities for innovative applications. Especially in robotics, improvements in terms of throughput, latency, and reliability are enabling new use cases that vary from remote teleoperation of mobile robots to edge processing of multi-robot fleet systems. These scenarios target the increase of energy efficiency, productivity and security of automated processes for industry. Verticals such as manufacturing are demanding due to the co-existence of humans and machines. These shared locations are sensitive to productivity issues such as deadlocks and bottlenecks for mobile robots, and security matters such as labor accidents. In this sense, mobile robots require the processing of sensor data to detect humans on time to avoid accidents. This application is limited by the computational costs to process data in robots using intelligent algorithms. Therefore, it is necessary to offload data from mobile robots to high-performance servers located in the network at lowest latency. From a communications perspective, this application provides a challenge to ensure that safety information, intended to avoid accidents, is transmitted properly while many elements are connected to the wireless network. Hence, the integration of slicing and edge processing capabilities remain essential to prioritize the offloading of robot sensor data. Following this scope, this work provides an evaluation of a current Network Slicing solution to support multiple stream for mobile robot applications, prioritizing an application of obstacle avoidance for human safety to showcase the relevance of slicing and edge process offloading capabilities in these scenarios.