Sang Kwon Han
Papers
5
Total Citations
136
H-Index
3
About
Sang Kwon Han is a pioneering researcher in agricultural robotics, whose work has fundamentally advanced the automation of weed control in paddy fields. His primary research areas center on autonomous navigation systems for agricultural robots, with a specific focus on vision-based guidance line extraction algorithms. Han’s most significant contribution is the development of a morphology-based guidance line extraction method for autonomous weeding robots, detailed in his highly cited 2015 paper (112 citations). This work enables robots to accurately follow crop rows in complex, wet paddy environments without damaging the rice, addressing a critical bottleneck in precision agriculture. By leveraging rice morphology characteristics and infrared vision sensors, Han’s algorithms improve the accuracy of central point detection in crop rows, allowing for effective, non-destructive weed control. His research also extends to robotic leg design, as seen in his work on a 3 DOF parallel delta-type leg for quadruped robots, which aims to maximize actuation torque reduction. With over 130 total citations, Han’s innovations are instrumental in increasing rice yield through sustainable, automated farming, making him a key figure in the intersection of computer vision, robotics, and agriculture.
Research Focus
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Top Papers
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