Cognitive Edge for Factory: a Case Study on Campus Networks enabling Smart Intralogistics

Abstract

Mobile autonomous transport systems are a crucial part of flexible factory logistics enabling an adaptable industrial production. Whereas connectivity of these mobile robots is still mostly covered through Wifi, applicators suffer from interferences and unreliableness due to the harsh environmental conditions. We present a case study using 4G campus networks applying network slicing technology and edge computing in order to realize a distributed control scenario. Control algorithms are offloaded to the edge following a navigation as a service approach. Basic safety functions remain onboard while self-localization and mapping as well as motion planning run on either a factory edge, a nearby edge or on a public cloud. We present an evaluation of the overall architecture and focus on effects of offloading control functions towards the edge. Finally, we provide an outlook towards the usage of 5G.