Bo-Nam Cha

Papers

Total Citations

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About

Bo-Nam Cha is a robotics researcher whose work centers on precision control and visual servoing, with a particular focus on enhancing the accuracy of robotic manipulators. His most-cited paper, "A study on visual feedback control of SCARA robot arm" (2015, 6 citations), makes a foundational contribution by systematically analyzing how increasing the number of visual features improves the accuracy of visual feedback control for SCARA robots. In this work, Cha derives critical rank conditions linking the image Jacobian to control performance, and formally proves that accuracy improves with a greater number of features—a result that has practical implications for industrial automation and assembly tasks. While his citation count reflects a focused, early-career impact, the theoretical rigor of his approach—connecting control theory, computer vision, and robotic kinematics—marks him as a methodical contributor to the field. Cha’s research is particularly valuable for students and engineers seeking to understand the mathematical underpinnings of visual servoing and the trade-offs involved in feature selection for real-time robotic control.