SLAM & State Estimation
Localization & Mapping
At the Intelligent Robots Lab (IRL), we focus on advancing intelligent robotics through research in Simultaneous Localization and Mapping (SLAM), Vision-Language-Action (VLA) models, Reinforcement Learning (RL), and Deep Learning, and other emerging areas in robotics.
We develop innovative algorithms and intelligent systems that enable robots to perceive and understand their environments, make autonomous decisions, and perform complex tasks in simulation and real-world scenarios. Our research aims to bridge the gap between robotic perception, learning, and action, pushing toward more autonomous, adaptive, and robust intelligent robots.
Our lab explores innovative approaches to intelligent robotics, focusing on robotic perception, autonomous navigation, and intelligent decision-making. We aim to develop robust, adaptive, and autonomous robotic systems that can perceive, understand, and interact with complex real-world environments.
Localization & Mapping
Dense 3D reconstruction
Robot Navigation & Control
3D Semantic Mapping & Scene Understanding
Localization & Mapping
Dense 3D reconstruction
Robot Navigation & Control
3D Semantic Mapping & Scene Understanding
Robot navigation & Learning-based method
Bridging vision, language and action
Seeing and understanding
Multi-robot coordination
Our projects bring together robotics, AI, and autonomous systems to develop practical technologies that address challenging real-world applications. We turn innovative ideas into intelligent robotic solutions.
Semantic 3D maps that let robots find objects and plan where to go.
Real-time SLAM that fuses LiDAR, camera and IMU, with dense 3D reconstruction.

Robots that share what they see to recognize places together.