LG CNS brings global robotics experts together to advance physical AI
Summary
LG CNS hosted its 2026 Robotics & Physical AI Forum at its Future Robotics Lab headquarters in Magok, Seoul, bringing together more than 100 researchers and industry professionals to discuss deploying physical AI in industrial settings. The company presented its approach to applying robotics in factories and logistics operations and introduced its PhysicalWorks Forge and PhysicalWorks Baton platforms. Participants discussed robot foundation models, data, hardware, simulation and challenges in real-world deployment. LG CNS said it hopes continued engagement with academia will help turn research into industrial innovation.
Key Facts
- Participants included faculty members, graduate students and company employees from the University of Toronto, Sogang University, Chung-Ang University and Korea University.
- LG CNS said it has more than two decades of experience and has completed over 1,000 smart factory and smart logistics projects.
- PhysicalWorks Forge is a robot-learning platform, while PhysicalWorks Baton uses agentic AI for robot operations and management.
- University of Toronto Professor Lee Chi-geun discussed combining data from different types of robots, flow matching and action chunking to help robots produce smoother, more continuous movements.
- The presentation identified differences in robot movement, latency and data availability as challenges for deploying robot foundation models.
Global robotics experts and LG CNS specialists discuss physical artificial intelligence developments and industrial applications during the 2026 Robotics & Physical AI Forum at the company's Future Robotics Lab in Seoul. Courtesy of LG CNS
LG CNS brought together more than 100 researchers and industry professionals to explore how physical artificial intelligence (AI) can move beyond laboratories and into factories, warehouses and other industrial settings.
The company recently hosted its 2026 Robotics & Physical AI Forum at its Future Robotics Lab headquarters in Magok, Seoul, with participants including faculty members, graduate students and company employees from the University of Toronto, Sogang University, Chung-Ang University and Korea University.
Discussions focused on advances in robot foundation models, data, intelligent robotic hardware and simulation, as well as technical challenges involved in deploying physical AI in real-world operations.
Drawing on more than two decades of experience and over 1,000 smart factory and smart logistics projects, LG CNS presented its approach to bringing robotics technologies into industrial environments.
The company also introduced two platforms launched this year: PhysicalWorks Forge, a robot-learning platform, and PhysicalWorks Baton, an agentic AI-based platform for robot operations and management.
Professor Lee Chi-geun of the University of Toronto presented research on the development of robot foundation models and technologies needed to deploy them in physical robots.
He discussed methods for combining data from different types of robots, along with flow matching and action chunking, techniques designed to help robots generate smoother, more continuous movements.
Differences in robot movement, latency and data availability remain among the challenges facing the technology, according to the presentation.
Participants also exchanged views on applications in manufacturing and logistics, operational challenges, the capabilities companies and universities need to develop, and how human roles may evolve as robotics advances.
"We hope to strengthen our technological competitiveness through continued engagement with academia and build our business capabilities so research results can lead to innovation in actual industrial settings," said Lee Jun-ho, executive vice president and head of LG CNS' Smart Logistics & City Business Division.
This article was published with the assistance of generative AI and edited by The Korea Times.
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