Robotics Transformation
Future Robotics LAB is a research organization under the CTO that brings together LG CNS’s Physical AI experts. AI engineers, robotics engineers, and researchers work together in one organization to deliver end-to-end Physical AI.
RX is a role that enables robots to perform tasks previously handled by people in industrial sites. It analyzes on-site work, secures, organizes, and augments data that robots can learn from, and rapidly develops RFM (Robot Foundation Model) capabilities that can perform real tasks. The robot intelligence developed in this way is implemented as industry-specific solutions and connected to an operations platform so it can be run efficiently in the field.
Rather than simply developing robots, RX uses robots as an actual workforce to maximize productivity at industrial sites.
We develop a Physical AI learning platform that can quickly train robots needed in the field and deploy them immediately. We directly handle everything from data collection, generation, augmentation, curation, and training automation to building post-training and fine-tuning environments. This creates a structure where robot learning does not start from scratch for each new project, but continues to build on the platform.
This team builds an integrated platform that goes beyond operating a single robot well and transforms entire factories, logistics centers, and cities into one Software Defined Environment. It manages multi-vendor, multi-type robots, from fixed automation equipment to AGVs, AMRs, and humanoids, under a single system. It also optimizes overall operational efficiency through task scheduling and Fleet Management.
For robots to work in the field, they need to move, navigate, and manipulate objects. This team researches and advances core technologies in locomotion, navigation, and manipulation. It also establishes model training frameworks based on industrial scenarios and raises RFMs to the level where they can perform real field tasks.
We develop automation solutions that can be used in real industrial sites through humanoid and intelligent robots equipped with RFMs. We develop automation solutions for a wide range of fields, including manufacturing, logistics, autonomous patrol, data center operations, and smart city services. We train robots using industry-specific work data and implement them in a form that can be deployed immediately.
The RX role consists of the following specialized tracks.
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This role handles the implementation and integration of robot perception, decision-making, and control functions, the development of control algorithms and motion/path planning, and the design and on-site debugging of ROS-based operating software.
It is suited for those with experience in C++/Python/ROS(ROS2)-based robot software development, motion planning, SLAM, autonomous driving, and robot vision.
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This role handles the design and verification of robot mechanisms, electrical systems, and drive units, HW/SW integration, system maturity, prototype production, assembly, and on-site installation.
It is suited for those with experience in mechanical design (CAD), electrical design, integrated testing, and on-site commissioning.
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This role handles the application of Robot Foundation Models to robot systems, model design, tuning, and training pipeline implementation, as well as simulation, teleoperation, and robot data preprocessing.
It is suited for those with experience in PyTorch/TensorFlow-based model training, reinforcement learning, vision AI, or multimodal AI.
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This role handles the design of integrated operations platforms for multi-vendor, multi-type robots, Robot Fleet Management architecture design, and the development of task scheduling and resource optimization algorithms.
It is suited for those with experience in distributed system design, MSA-based platform design, and cloud-based operations platforms.
RX is not just about developing robots. It is about redefining how industries operate. If you are interested in rethinking industrial problems through technology, exploring the convergence of robotics and AI, building technology that works in real-world sites, and creating new standards for the Physical AI era, apply now.
