Papers
6
Total Citations
73
H-Index
4
About
Seokju Lee is a researcher at the forefront of intelligent vehicle systems and mobile robotics, with a core focus on multi-sensor fusion, real-time object detection, and cost-effective localization. His most impactful contribution is a pioneering framework for fast multiple objects detection and tracking (DATMO) that fuses color camera data with 3D LIDAR, specifically designed to overcome the high computational complexity that hinders real-world deployment. This work, cited 46 times, has become a key reference for engineers seeking practical, low-latency perception in autonomous driving. Lee has also made significant strides in democratizing multi-robot systems, developing a vision-based localization method that leverages a single, low-cost camera to achieve accurate indoor positioning—a breakthrough for resource-constrained platforms. Further demonstrating his versatility, he has innovated by repurposing a smartphone as a robot’s central processing unit, integrating rotating ultrasonic sensors for indoor navigation and localization. His work on an exploration rover for sample return missions also showcases his commitment to advancing autonomous navigation in challenging, unstructured environments. Lee’s research consistently bridges the gap between theoretical algorithms and deployable, real-time solutions.
Research Focus
Key Achievements
Top Papers
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- 5Development of an exploration rover platform for sample return mission2 citations · 2014
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