LG CNS discussed ways to apply physical AI in industrial settings with domestic and international robotics researchers.
On Thursday, LG CNS announced that it recently held the "2026 Robotics & Physical AI Forum" at its "Future Robotics Lab" located at its Magok headquarters in Seoul.
The event was attended by over 100 people, including faculty members and graduate students from the University of Toronto, Sogang University, Chung-Ang University, and Korea University, as well as LG CNS executives and employees.
Participants shared research updates and industrial application challenges regarding core physical AI technologies, such as robot foundation models (RFM), data, intelligent robot hardware, and simulation.
Based on its experience with over 1,000 smart factory and smart logistics projects conducted over more than 20 years, LG CNS introduced the direction for industrial applications of physical AI.
The company also unveiled "Physical Works Pose," a robot learning platform launched this year, and "Physical Works Baton," a robot operation and control platform based on agentic AI.
Global researchers shared their latest research findings, focusing on robot intelligence and control technology. Professor Lee Chi-geun of the University of Toronto explained the development process of robot foundation models and the technologies required for actual robot applications.
He introduced methods for utilizing data from different robots together, as well as flow matching and action chunking techniques to make robot movements natural. The issues of varying movements, latency times, and data acquisition across different robots were presented as future challenges to be resolved.
Participants also exchanged views on technical and operational challenges for the stable introduction of robots in manufacturing and logistics sites, the capabilities that companies and universities must acquire, and the role of humans in the era of robotics.
Lee Jun-ho, Senior Executive Vice President and Head of the Smart Logistics & City Business Division at LG CNS, stated, "We will continuously exchange ideas with academia to strengthen our technological competitiveness and enhance our business capabilities so that research outcomes lead to innovation in actual industrial sites."
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