RILS Lab

Welcome to Robot Intelligence Learning & System Lab!

The Robot Intelligence Learning & System (RILS) Lab focuses on advancing Physical AI—intelligence that is embodied in the physical world. Our goal is simple yet ambitious: to make robots truly intelligent.

Intelligence in robotics goes beyond perception or control alone. To make robots smarter, they must:

• Perceive the physical world accurately and robustly
• Understand and adapt to dynamic, uncertain environments
• Learn from interaction and experience
• Make optimal decisions in real time
• Act safely and efficiently in the real world

To achieve this, we integrate deep learning-based vision, reinforcement learning, and robot system design into a unified framework for intelligent robotic behavior. By tightly coupling perception, learning, and control, we develop autonomous systems capable of continuous adaptation and long-term decision-making in complex real-world environments.

Our research drives innovation in autonomous robots, unmanned vehicles, intelligent automation systems, and end-to-end learned robotic platforms, pushing the boundaries of Physical AI.

Research Areas

• Robotics(
• Deep Learning Vision
• End-to-End Driving
• Reinforcement Learning