Chang‐Hun Lee
Papers
4
Total Citations
64
H-Index
4
About
Chang-Hun Lee is a robotics researcher whose work centers on sensor data fusion and vision tracking for mobile robots. His major contributions lie in developing advanced localization and tracking systems that integrate data from multiple sensors to overcome the challenges of dynamic robot motion. His most-cited paper, "Sensor data fusion using Unscented Kalman Filter for accurate localization of mobile robots" (2010, 39 citations), presents a novel UKF-based method that significantly improves localization accuracy by fusing sensor inputs. Lee also pioneered a high-performance vision tracking system using Kalman filter-based sensor fusion (13 citations) and introduced a biologically inspired approach in "Sensor data fusion using fuzzy control for VOR-based vision tracking system" (8 citations), which mimics the human eye's vestibulo-ocular and opto-kinetic reflexes to maintain robust tracking under dynamic conditions. His work on pan/tilt camera control (4 citations) further extends these capabilities. With a cumulative 64 citations across his key papers, Lee has established himself as a contributor to intelligent robotics, particularly in enabling robots to perceive and navigate their environments with greater accuracy and reliability.
Research Focus
Key Achievements
Top Papers
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