Do‐Young Lee

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About

Do-Young Lee is a robotics researcher whose work centers on autonomous navigation, obstacle avoidance, and multi-agent robotic systems. His research addresses one of the fundamental challenges in modern robotics: enabling robots to perceive and safely navigate complex, unknown environments in real time. Lee's most notable contribution is his development of a 3D vision-based local obstacle avoidance system for humanoid robots, which leverages Speeded Up Robust Features (SURF) and panoramic environment mapping to allow robots to dynamically determine avoidance direction and walking motion. This work, cited 9 times, demonstrates a sophisticated integration of computer vision and locomotion planning in humanoid platforms. Complementing this, his research on multi-agent obstacle avoidance combines infrared sensor data with image processing to enable robots to share spatial information in real time, facilitating more efficient cooperative path planning in industrial and scouting applications. Together, these contributions reflect Lee's focus on building intelligent, sensor-fusion-driven systems that push the boundaries of autonomous robot behavior. While his citation footprint remains emerging, his work provides meaningful groundwork for researchers developing practical navigation solutions in humanoid and collaborative robotic systems.