5G and beyond 5G technologies enabling Industry 5.0: network applications for robotics

Abstract

The convergence of cloud and edge computing, along with distributed AI and the latest 5G/6G communications, is revolutionizing collaboration, connectivity, and interaction. These digital advancements pave the way for a new era of AI-powered robots, enabling them to navigate unfamiliar scenarios and adapt in the long term by seamlessly engaging with the digital realm. Consequently, these innovative applications generate diverse, continuous, and rapidly evolving data transmission requirements that traditional network resource management struggles to satisfy in terms of Quality of Service (QoS). In this paper, we take a step beyond focusing solely on network-side traffic engineering efforts. Instead, we explore the potential of application-side traffic shaping within non-public networks to address these demanding transmission needs. Within the framework of optimizing Quality of Experience, we discuss on how the 5G-ERA project focuses on a multi-domain learning process for autonomous robotics using an intent-based networking approach for optimized resource management within the network validated by the use cases within the project enabling the transition from Industry 4.0 to Industry 5.0. Our central aim is to efficiently control and direct data traffic within the confines of the private network, ensuring it aligns with predefined objectives. While this methodology can be applied in various contexts, it is essential to establish precise intentions rooted in domain expertise. This innovative approach serves as a valuable complement to conventional network resource management methods typically employed at the network infrastructure level.

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