Papers
3
Total Citations
17
H-Index
2
About
Jiyong Oh is a robotics researcher whose work centers on autonomous mobile robot localization, sensor fusion, and redundancy control. His most impactful contribution, "FusionLoc: Camera-2D LiDAR Fusion Using Multi-Head Self-Attention for End-to-End Serving Robot Relocalization" (2023, 9 citations), addresses a critical challenge in service robotics: enabling robots to reliably determine their position in dynamic indoor environments. By integrating camera and LiDAR data through a multi-head self-attention mechanism, Oh’s approach achieves robust end-to-end relocalization—a key enabler for serving robots that became increasingly vital during the COVID-19 pandemic. His earlier foundational work, "Analysis of Singularity and Redundancy Control for robot-Positioner System" (1989, 7 citations), explores kinematic control for robotic manipulators, demonstrating long-standing expertise in robot motion planning. Most recently, Oh has advanced uncertainty-aware localization (2025), proposing a percentile-based rejection method that improves localization reliability without altering the underlying prediction model. With a career spanning from classical redundancy control to modern deep learning-based sensor fusion, Oh’s research bridges foundational robotics theory and practical deployment challenges. His work has direct implications for autonomous navigation in hospitals, restaurants, and other human-centric environments, making him a notable contributor to the field of service robotics.
Research Focus
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