Eung-Su Kim

Papers

Total Citations

H-Index

About

Eung-Su Kim is a researcher at the forefront of sensor fusion and robotics, with a focus on enhancing the safety and autonomy of complex systems. His key research areas include multi-sensor calibration, LiDAR data processing, and human-robot collaboration. Kim’s most impactful contribution is his work on extrinsic calibration of camera-LiDAR systems using a planar chessboard (2019), a method that has garnered 35 citations for enabling precise data fusion in computer vision and robotics. This foundational technique supports advancements in autonomous navigation and 3D perception. He has also developed a weighted median filter for upsampling low-resolution LiDAR data (2021), improving sensor performance in cost-constrained applications. Notably, Kim’s recent work (2023) addresses a critical safety challenge: automating the transport and loading of heavy ammunition in indoor firing ranges. By integrating autonomous transport with robotic loading, his system reduces human exposure to hazardous environments, showcasing a practical application of human-robot cooperation. With a growing citation record and a clear trajectory toward impactful, real-world solutions, Kim is a rising figure in robotics and sensor systems.