RS Automation Seeks to Build K-Robot Component Ecosystem with Agentic Robotics

RS Automation, a company specializing in robot motion and energy control, is set to build an ecosystem connecting domestic robot component companies through an Agentic Robotics platform that combines artificial intelligence (AI) and precision motion technology. The plan is to establish a foundation for applying a range of components to actual robots and production equipment and jointly verifying their performance, going beyond localizing individual components.

RS Automation said it plans to build an Agentic Robotics platform by combining AI learning capabilities with its proprietary precision motion technologies, including motion control, servo drives, and encoders.

Agentic Robotics is an approach in which AI analyzes work objectives and a robot's operating status to determine the actions needed, then makes adjustments and learns autonomously based on data collected during execution. RS Automation aims to support the implementation of Physical AI for use in real-world settings by connecting higher-level AI task intelligence with lower-level precision control technologies.

To this end, AI will use as prior knowledge not only the characteristics of motors and reducers but also differences in load inertia, friction, stiffness, and transmission mechanisms such as belts and ball screws. It will then use data accumulated during actual operation to adjust motion conditions, while the lower-level control system applies the learned decisions to real-time operation.

The key is to reduce the burden of having to learn all motion conditions through trial and error from scratch and to secure motion performance suited to the equipment and working environment more efficiently.

Once the platform is complete, joint testing and integrated deployment among domestic robot component companies are also expected to become possible. The plan is to enable companies in fields such as motors, reducers, encoders, servo drives, actuators, and robot hands to connect their products using common interfaces and performance evaluation systems, and to verify motion performance across different combinations.

The company says this approach will differ from conventional component evaluation methods because it will allow the joint verification of precision, responsiveness, and force-control performance required for actual robot tasks, rather than simply comparing specifications for individual components.

RS Automation sees humanoid robots and AI factories as key application areas. Precision motion technology is important for humanoid robots because they must precisely control multiple joints simultaneously. AI factories, meanwhile, need robots that can adapt flexibly to changes in products and manufacturing processes.

The company believes that technology for continuously adjusting robots' motion performance using data accumulated in real-world settings could determine the competitiveness of both fields.

RS Automation plans to expand collaboration with domestic component companies and robot and equipment companies, with the Agentic Robotics platform at its center. Its goal is to enhance the technological competitiveness of Korea's robotics industry by linking AI learning and control technologies not only to component integration but also to deployment in actual equipment.

An RS Automation representative said, "RS Automation's Agentic Robotics platform aims to serve as a platform connecting domestic component companies with robot and equipment companies, built on precision motion technology. We will enhance the competitiveness of Korea's robot component ecosystem by advancing AI learning and control as well as integrated verification, going beyond the localization of individual components."

This content was produced with the assistance of AI translation services.