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About

Chin Su Kim is a robotics researcher whose work spans autonomous mobile systems, robust control theory, and vision-based manipulation. With a career focused on bridging perception and control, Kim has made meaningful contributions to the challenge of operating robotic systems reliably under real-world uncertainty. His most cited work, "Obstacle Avoidance of a Mobile Robot Using Vision System and Ultrasonic Sensor" (2007, 21 citations), demonstrated practical techniques for fusing visual and acoustic sensing to enable safer autonomous navigation. Alongside this, Kim developed a sustained research program in robust control of robot manipulators, culminating in his 2011 paper on dynamic compensators under parametric uncertainty (10 citations), which proposed a novel feedback controller improving transient response and accelerating tracking error convergence for n-link robotic arms. Earlier iterations of this framework, including image-based variants addressing Jacobian uncertainty, reflect Kim's systematic approach to validating and extending his methods across different sensing modalities. Collectively, his publications underscore a commitment to making robotic systems more resilient, precise, and adaptable — contributions that remain relevant to researchers working at the intersection of control engineering and intelligent robotics.