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About

Boseong Kim is a robotics researcher whose work centers on autonomous navigation, localization, and mapping for robots operating in complex, GPS-denied environments. His major contributions include developing a LiDAR Inertial Odometry (LIO) algorithm with adaptive keyframe generation, enabling fast and accurate state estimation for both aerial and ground robots in challenging underground spaces. He also designed an assistive delivery robot for real-world postal services, using 3-D point cloud map matching to navigate urban apartment complexes without GPS—a paper that has garnered 59 citations. Kim’s impact extends to high-stakes applications: he contributed to Team KAIST’s autonomous racing system for the Indy Autonomous Challenge, pushing the limits of perception and control at high speeds, and to Team CoSTAR’s NeBula solution for the DARPA Subterranean Challenge, scaling autonomy to larger environments. His recent work on autonomous UAV exploration and tracked robot reconnaissance in multi-floor indoor settings further demonstrates his commitment to practical, real-world deployment. With over 100 total citations and a growing portfolio of field-tested systems, Boseong Kim is advancing the frontier of resilient, lightweight autonomy for robots in the most demanding conditions.