SKT announced on the 7th that it has successfully completed a demonstration of autonomous driving robot technology based on its Telco Edge AI infrastructure.

SKT's goal for this demonstration was to secure core technologies for indoor product transport and delivery robots that require high-precision positioning. It was conducted at SKT's Pangyo office for two months starting in June of this year.

SKT has autonomous robots perform various tasks based on the Telco Edge AI infrastructure built in its headquarters. The robots moving through the complex interior of the headquarters processed various information received from sensors such as cameras and IMUs (Inertial Measurement Units) based on AI technology.

The company applied its VLAM (Visual Localization And Mapping, image-based sensor fusion positioning and spatial data generation technology) to the robot's autonomous driving. VLAM is an AI-based positioning technology that analyzes camera footage mounted on a robot in real time to identify its precise location and support the robot's stable movement even in complex environments.

SKT said, “The Telco Edge AI infrastructure linked to the robot played a significant role in maximizing the accuracy and efficiency of the autonomous driving robot and improving service performance.”

In an environment where a large number of robots move at high speeds, the importance of real-time precise positioning and real-time AI inference is expected to increase further. The Telco Edge AI infrastructure explains that it can increase the value of mobile networks by reducing the burden of computation concentrated in the cloud through edge computing and performing real-time AI inference by combining AI solutions.

In particular, the Telco Edge AI infrastructure is expected to be able to replace existing high-cost on-device vision AI equipment. Edge AI is suitable for protecting personal information and strengthening data security by processing data collected by robots immediately at the edge without sending it to a central server.

Edge AI can also be used to safely protect sensitive information by reducing the risk of hacking or data leakage. Efficiency can also be improved by updating only edge servers rather than individual robots.

SKT added that edge AI can improve the object recognition capabilities of autonomous robots and process path calculation tasks in real time, thereby reducing the burden on robot hardware and minimizing battery consumption.

SKT plans to actively develop various business models based on Telco Edge AI. It is expected to lead to innovation in various fields such as manufacturing, logistics, and service industries, and become the foundation for meeting the increasingly complex and diverse market demands in the future.

SKT aims to lead technology standardization by emphasizing Telco Edge AI infrastructure. At the 3GPP workshop held last May, it suggested the importance of Telco Edge AI infrastructure and the need for standardization, securing a consensus from global operators, and at the O-RAN Alliance standards meeting held last June, it also proposed standardization of Telco Edge AI infrastructure.

SKT plans to build a testbed to provide an environment for testing the performance and effectiveness of edge AI-based technologies, products, and services, and to secure the technology required to design a telco edge AI infrastructure suitable for the mobile carrier environment. In addition, it plans to proactively promote the expansion of the telco edge AI ecosystem through diverse research and development activities and technology verification, such as global standardization, cooperation between operators, manufacturers, and academia, securing intellectual property rights, and publishing papers.

Ryu Tak-ki, head of SK Telecom’s infrastructure technology division, said, “Through this demonstration, we have laid the foundation for applying Telco Edge AI-based security technology and low-latency services to various industries.” He added, “We will lead the evolution of 6G AI wired and wireless infrastructure that adds new value to infrastructure by converging communications and AI in terms of technology development, global standardization, and ultra-cooperation.”