Wan Shik Jang
Papers
4
Total Citations
11
H-Index
2
About
Wan Shik Jang is a robotics researcher whose work centers on robot vision control, flexible robot manipulation, and the development of robust algorithms for uncertain industrial environments. His major contributions include pioneering an open-loop control scheme to minimize residual vibrations in flexible robots (2003), and advancing vision-based control through the application of Newton-Raphson (N-R) and Extended Kalman Filter (EKF) methods. Jang’s research addresses critical challenges in real-world robot vision, such as camera calibration, focal length correction, and 3D-to-2D coordinate mapping, proposing a six-parameter camera model that enables effective control even when the relative position between camera and robot is unknown. His work on slender bar placement and obstacle-avoidance trajectory planning under uncertainty demonstrates practical solutions for discontinuous path generation. Though his citation counts are modest—ranging from 2 to 4 per paper—his contributions are notable for their focus on overcoming real industrial hurdles, such as dynamic obstacles and kinematic model inaccuracies. Jang’s research offers valuable insights for students and engineers interested in vision-guided robotics, flexible manipulators, and control strategies that thrive amidst uncertainty.
Research Focus
Key Achievements
Top Papers
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