Seunghwa Oh
Papers
2
Total Citations
8
H-Index
2
About
Seunghwa Oh is a researcher focused on advancing human-robot interaction, particularly through the development of intuitive motion-capture and teaching systems for humanoid social robots. His primary research area lies in inverse kinematics and the use of depth camera data to enable robots to learn and replicate human movements. Oh’s major contributions include the development of recursive inverse kinematic analysis methods that allow humanoid robots to be taught complex motions in real-time using non-invasive depth sensors, such as the Microsoft Kinect. This work is pivotal for creating more natural and friendly human-robot interactions, as it bypasses the need for cumbersome wearable sensors. His most cited papers, including "Recursive inverse kinematic analysis for humanoid robot based on depth camera data" (2021) and a related 2020 study, have each garnered 4 citations, establishing a foundational approach for teaching human motion to social robots. By focusing on the computational efficiency of recursive algorithms, Oh’s research directly addresses the challenge of enabling robots to fluidly mirror human gestures, a key step toward more empathetic and responsive robotic companions in social and service settings.
Research Focus
Key Achievements
Top Papers
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- 2