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About

Jung Hyun Oh is a robotics researcher whose work focuses on autonomous navigation, multi-robot coordination, and sensor-based perception. His most influential contribution is the development of a velocity obstacle-based local collision avoidance algorithm for holonomic elliptic robots, which has garnered 41 citations and provides a mathematically rigorous framework for safe robot motion in dynamic environments. Oh has also made significant advances in indoor localization, introducing an active infrared positioning system that leverages passive landmarks for high-accuracy, low-latency position estimation—a practical solution for mobile robots operating in GPS-denied spaces. In multi-robot systems, he proposed a cooperative object transportation method using parallel line formation with a circular shift, enabling teams of robots to manipulate and move objects without requiring precise grasping or complex iterative motions. More recently, Oh addressed a critical sensing challenge with a novel range-only measurement-based glass line feature extraction method, allowing low-cost LiDAR sensors to detect transparent objects without relying on intensity or multi-echo data. With a total of 68 citations across his most-cited works, Oh’s research bridges theoretical motion planning with real-world sensor limitations, offering practical solutions for autonomous systems.