Hanmin Lee

Papers

Total Citations

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About

Hanmin Lee is a researcher focused on autonomous mobile robotics, with a particular emphasis on perception and navigation in structured environments. His work addresses the critical challenge of enabling delivery robots to safely traverse urban landscapes by detecting subtle terrain features like curbs. Lee’s most cited paper, “Lidar Measurement Analysis for Detection of Down-Curbs and Up-Curbs” (2023), introduces a novel method for using LiDAR data to identify both downward and upward curb transitions—a key capability for robots moving between roads, sidewalks, and crosswalks. While his citation count is still growing, this work has laid important groundwork for improving the reliability of autonomous delivery systems in mixed-use pedestrian and vehicular spaces. Lee’s contributions are particularly notable for their practical focus on real-world deployment, addressing the gap between indoor and outdoor navigation. As the demand for last-mile delivery robots expands, his research offers a foundational approach to obstacle detection that enhances safety and operational efficiency.