Papers
1
Total Citations
7
H-Index
1
About
Cheonin Oh is a researcher whose work lies at the intersection of robotics, human-robot interaction, and acoustic signal processing. His key contributions focus on enabling robots to perceive and respond to their environments more naturally, particularly through sound source localization and tracking. In his most cited work, "The impulse sound source tracking using Kalman filter and the cross-correlation" (2006, 7 citations), Oh addresses a fundamental challenge in human-robot interaction: making robots move and act in ways that feel intuitive and close to human behavior. He proposes a weighted Kalman filter that leverages cross-correlation values derived from time difference of arrival (TDOA) measurements, significantly improving the accuracy and robustness of impulse sound source tracking. This work is foundational for robots that need to locate and follow sounds in real-time, enhancing their ability to interact seamlessly with people. Oh’s research demonstrates a clear commitment to bridging the gap between raw sensor data and natural robotic behavior, making his contributions valuable for students and engineers developing more responsive, human-aware robotic systems.
Research Focus
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Top Papers
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