Wook Bahn
Papers
9
Total Citations
47
H-Index
4
About
Wook Bahn is a robotics and sensor fusion researcher whose work centers on mobile robot navigation, vision-based target tracking, and multi-sensor data integration. His research, conducted primarily in the early 2010s, addresses one of the fundamental challenges in mobile robotics: enabling robots to accurately perceive, localize, and track moving targets in dynamic environments. Bahn's most significant contributions involve developing sophisticated vision-tracking systems that fuse data from stereo cameras, gyroscopes, wheel encoders, and inertial sensors to control pan-and-tilt actuators and maintain continuous line-of-sight with moving targets. His most cited work (2011, 13 citations) established a framework for integrating robot motion information with stereo vision, while subsequent research demonstrated the effectiveness of the Unscented Kalman Filter for robust state estimation. He also explored multi-robot tracking scenarios, enabling one moving robot to continuously track another — a particularly challenging problem in autonomous systems research. Beyond vision systems, Bahn contributed to MEMS sensor development, including a 16-bit tri-axis capacitive microaccelerometer for mobile applications. His cumulative body of work, spanning fuzzy logic controllers, Euler angle orientation methods, and 3D target tracking architectures, reflects a broad and technically rigorous approach to making mobile robots more perceptually capable and spatially aware.
Research Focus
Key Achievements
Top Papers
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- 3Mobile robot vision tracking system using Unscented Kalman Filter7 citations · 2011
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