Papers
3
Total Citations
17
H-Index
2
About
Seungbin Kim is a pioneering researcher at the intersection of hardware architecture, autonomous systems, and embedded artificial intelligence, with a specialized focus on LiDAR-based Simultaneous Localization and Mapping (SLAM) for mobile robotics and autonomous driving. His work addresses a critical gap in the field: the inadequacy of camera-based SLAM processors for real-world autonomous navigation, which demands wide field-of-view sensing, accurate 3D depth perception, and 360° environmental awareness. Kim's most notable contributions include the development of highly integrated, energy-efficient SLAM System-on-Chip (SoC) architectures that combine point neural network (PNN)-based 3D semantic segmentation with multi-level k-nearest neighbor (kNN) acceleration. His LSPU processor represents a landmark achievement in real-time LiDAR SLAM hardware, enabling mobile robots to perceive, localize, and map complex environments with minimal power consumption. By fusing AI-driven perception with spatiotemporal-aware computing, his designs significantly reduce pose estimation errors — a fundamental challenge in autonomous navigation. With multiple publications in 2024 accumulating nearly 17 citations, Kim is rapidly establishing himself as an emerging authority in intelligent robotics hardware, making sophisticated autonomous systems more practical and deployable across real-world platforms.
Research Focus
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Top Papers
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