Jeonbuk National University (JBNU) has been selected as a key research and demonstration institution for the large-scale national Physical AI R&D program that the government is promoting with KRW 820 billion in funding. The support amounts to a total of KRW 265.18 billion over five years, the largest share among participating institutions.

JBNU was selected for major research and infrastructure-construction tasks under the "Collaborative Intelligence Physical AI-Based Software Platform R&D Ecosystem Project." The university announced it will implement an end-to-end program over the next five years through 2030, covering core Physical AI technology development, manufacturing and logistics field demonstration, and the construction of large-scale research and demonstration infrastructure.

The project will be carried out from 2026 to 2030. According to the final project proposal, the total project budget is approximately KRW 826.6 billion, comprising KRW 506.5 billion in national funding, about KRW 86.0 billion in local funding, and roughly KRW 234.1 billion in institutional contributions.

Of this total, the scale of R&D, demonstration, and infrastructure projects that JBNU will directly execute or build in cooperation with partner institutions amounts to KRW 265.18 billion. This includes approximately KRW 118.48 billion in national funding, about KRW 82.18 billion in local funding, and roughly KRW 64.53 billion in institutional contributions.

JBNU will serve as the lead or a participating institution in core R&D and infrastructure projects of the program, including the development of collaborative-intelligence Physical AI core software, the construction of large-scale manufacturing and logistics testbeds, and the establishment of an open research cluster.

The project aims to realize "collaborative-intelligence Physical AI," which goes beyond applying existing AI technologies to individual robots or equipment. It seeks systems in which diverse robots, manufacturing equipment, and logistics systems can perceive their surrounding environment, assess situations, and cooperate to perform complex tasks.

To this end, JBNU will develop SDF-OCS (Software Defined Factory–Operation & Control System), a software-based system that integrates, links, and controls AI, robots, manufacturing equipment, and production and logistics systems. The university will also pursue development of core collaborative-intelligence Physical AI software technologies that can respond proactively to changes in production conditions and environments.

The Physical AI technologies and software developed through this project will be applied to manufacturing and logistics testbeds for integrated verification. The plan is to progressively verify and advance not only the performance and stability of individual technologies but also the connectivity and interoperability among robots, manufacturing equipment, and logistics systems, as well as their applicability in real industrial settings.

A large-scale Physical AI testbed construction project worth KRW 190.0 billion will be pursued in parallel. As a core participating institution, JBNU will build a demonstration infrastructure that links AI with industrial and collaborative robots, autonomous mobile robots, manufacturing equipment, and logistics systems, enabling comprehensive verification of Physical AI technologies in environments similar to actual manufacturing sites.

In particular, JBNU plans to proactively establish a testbed in temporary on-campus facilities before the completion of the open research cluster, allowing R&D and demonstration activities to proceed from the initial stages of the project. This approach will ensure continuity of research and demonstration during the cluster construction period and enable rapid verification and advancement of various Physical AI technologies developed under the main project.

The temporary on-campus testbed at JBNU will link various robots, manufacturing and logistics equipment, AI vision, digital twin, and AI computation and control environments to create a technology verification environment similar to a production site. Robot, sensor, vision, equipment, and production data obtained during demonstrations will be reused for R&D, establishing a cyclical R&D process of "technology development → demonstration → data acquisition → technology advancement → re-demonstration."

Alongside this, a KRW 78.4 billion "Collaborative-Intelligence Physical AI Open Research Cluster Project" will create a large-scale research and demonstration platform that connects Physical AI R&D, AI computation and verification, manufacturing and logistics demonstration, and shared corporate use.

The open research cluster will include three core facilities—a Joint R&D Center, an NPU Technology Demonstration Station, and a Demonstration Metafactory—linking Physical AI R&D, AI computation and verification, digital-twin-based pre-verification, and manufacturing and logistics demonstration into a single system.

JBNU will reflect the demonstration experience and the equipment, space, infrastructure, and data linkage requirements accumulated through operation of the temporary on-campus testbed in the design of the research cluster, thereby creating a research and demonstration environment with practical usability and scalability.

The experience accumulated in JBNU’s existing Physical AI Technology Demonstration Lab will also be actively used in the main project. The AI–robot–manufacturing-equipment integration technologies and demonstration experience developed in the demonstration lab will be applied to the temporary on-campus testbed and then gradually expanded into the large-scale research and demonstration environment of the open research cluster.

Accordingly, JBNU’s Physical AI research and demonstration system will be progressively advanced through the stages of "existing Physical AI Technology Demonstration Lab → temporary on-campus testbed → open research cluster."

JBNU will also strengthen industry–university–research cooperation to ensure that research outcomes do not remain at the paper or prototype stage but are disseminated into actual industrial sites.

The university plans to integrate Physical AI technologies into Jeonbuk’s key industries—automotive parts, commercial and special-purpose vehicles, agricultural machinery, machining, and manufacturing and logistics—and support local companies to conduct sufficient pre-verification and demonstration before applying new AI and robot technologies to production lines.

Yang O-bong, President of JBNU, said, "This project is significant because, based on JBNU’s accumulated research capabilities in AI, robotics, and smart manufacturing, it will establish a national research hub that connects Physical AI—from R&D to demonstration and industrial diffusion. We will actively share the university’s research personnel, technologies, and infrastructure with local companies and domestic industry–university–research partners to create an open innovation ecosystem where new technologies and industries are continuously generated."

He added, "Physical AI is a future core technology in which AI combines with robots and equipment in real manufacturing sites and industrial spaces to create new added value. JBNU will concentrate institutional capabilities to successfully carry out this national project and help Jeonbuk emerge as a key hub leading Korea’s Physical AI R&D and industrial innovation."

Kim Sun-tae, Director of the JBNU Physical AI Convergence Technology Project Group and Professor in the Department of Software Engineering, stated, "This selection is meaningful because JBNU has secured a foundation that connects core Physical AI technology development, real manufacturing-site demonstration, and the construction of large-scale research and demonstration infrastructure. We will integrally verify and advance the diverse technologies developed in the main project through the testbeds, establishing a system that enables rapid diffusion of research outcomes into actual industrial sites."

He added, "We will prioritize establishing a testbed on the JBNU campus before the open research cluster is completed, enabling concurrent R&D and demonstration from the early stages of the project. We will expand the experience accumulated in the current demonstration lab into the temporary testbed and the future open research cluster to build an open Physical AI R&D and demonstration ecosystem where R&D and demonstration continue without interruption, contributing to Jeonbuk’s growth as a central hub of Korea’s Physical AI industry."