Hong-Ju Kim

Korea Electrotechnology Research Institute

Papers

Total Citations

H-Index

About

Hong-Ju Kim’s research lies at the intersection of robotics, intelligent control, and precision manufacturing, with a focus on enhancing the capabilities of robotic systems for complex industrial tasks. His most cited work, a 2018 study on neural network-based adaptive actuator fault detection for robot manipulators (44 citations), introduces a robust algorithm that improves safety and reliability in automated systems—a critical contribution to the field of fault-tolerant control. Kim also made notable strides in manufacturing robotics, co-developing a hexapod robot designed for machining applications, which offers a larger workspace than traditional CNC machines while maintaining precision. This work challenges conventional approaches by prioritizing scalability and flexibility in machining platforms. Additionally, Kim contributed to mechanical system analysis with a hybrid frequency response method combining swept-sine and stepped-sine excitation, enabling more accurate non-parametric testing of robot and mechanical systems. Though his citation counts reflect a focused, emerging impact, his work demonstrates a clear trajectory toward practical, high-performance robotic solutions. Kim’s research is especially relevant for students and engineers interested in adaptive control, fault detection, and the next generation of machining robotics.