Jeong Seob Kim

Papers

Total Citations

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About

Jeong Seob Kim is a robotics researcher whose work centers on the intersection of visual servoing, neural control, and human-robot interaction. His most cited paper (2007, 5 citations) introduces a stereo visual feedback system for tracking moving objects with robot manipulators, establishing a foundational eye-in-head control architecture. Kim’s research demonstrates a consistent focus on embedded, real-time control systems, as evidenced by his implementation of a radial basis function (RBF) neural network on an FPGA chip for joint control of the ROBOKER arm (2009, 3 citations). This work represents an early integration of neural processing with hardware-level control. His third notable contribution (2008, 3 citations) extends this expertise into physical human-robot interaction, presenting an embedded position-based impedance force controller for the ROBOKER dual-arm robot. By combining robust position control with force regulation on an FPGA platform, Kim addressed the critical challenge of safe and responsive human-robot collaboration. Though his citation counts are modest, his contributions are technically significant for their pioneering use of FPGA-embedded neural and impedance controllers in robotic systems, offering practical pathways for real-time, adaptive robot control.