Evaluation of 5G Edge and Cloud Computing for Data Processing in Visual Referencing of Mobile Robot Manipulators

Abstract

To fit the requirements of growing flexibility in production processes, intralogistics is increasingly automated, for example, by Mobile Robot Manipulators, which can transport material and perform assembly tasks. However, these transport systems have limited battery capacity and recharging involves occasional downtime. New approaches, such as Edge Computing, offer transport systems to offload intensive computational processes, e.g., for path planning or AI-based image analysis, and thus saving precious energy resources. However, since offloading such processes onto a server is tied to high security and transmission requirements, using 5G for communication might be an attractive solution. Therefore, an exemplary referencing use case of a Mobile Robot Manipulator is presented and the 5G based communication with two cloud servers and one edge server is examined. Our experimental results show that with a mean transmission time of 540 milliseconds Edge Computing facilitates both faster and more stable data transmission compared to Cloud Computing with a mean transmission time of 1,973 milliseconds. This has a significant impact on industrial processes whose efficiency and productivity depend on the quality of data transfer.