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About

Jung-Hee Kim is a robotics researcher whose work sits at the intersection of autonomous navigation, sensor fusion, and human-robot interaction. Her primary research areas include simultaneous localization and mapping (SLAM), particularly range-only SLAM (RO-SLAM), and noise suppression for sound source localization in mobile robotics. Kim’s most significant contributions lie in advancing cooperative SLAM algorithms. She pioneered the use of the Sum of Gaussian (SoG) filter for cooperative dynamic range-only SLAM, achieving a computationally efficient solution that actively leverages inter-node measurements—a key improvement over traditional static-node approaches. Her work on Rao-Blackwellized particle filters for cooperative RO-SLAM further extended the field’s capabilities. In the domain of auditory perception, she developed a multi-input multi-output (MIMO) noise suppression algorithm that preserves spatial cues, enabling robust sound source localization for mobile robots despite ego-noise from motors. Her most cited paper (11 citations) addresses this challenge, while her SLAM papers collectively garnered over 20 citations. Kim also contributed to novel hardware design, co-developing an omni-directional mobile base using spherical robots as wheels. Her research is particularly impactful for applications in dynamic, real-world environments where robots must navigate and interact autonomously.