Jihong Min

Papers

Total Citations

142

H-Index

About

Jihong Min is a leading roboticist specializing in autonomous navigation, off-road perception, and field robotics. His research focuses on enabling mobile robots to operate safely in unstructured, hazardous environments—from rough terrain to battlefields. Min’s foundational work on probabilistic traversability mapping using 3D-LIDAR and camera fusion (75 citations) introduced a robust framework for estimating terrain passability without extensive training data, a critical advance for outdoor robots. He further demonstrated real-world impact through the development and control of HURCULES, a military rescue robot designed for casualty extraction (62 citations), showcasing his ability to translate theory into life-saving hardware. Most recently, Min has pushed the frontier of semantic mapping with uncertainty-aware Bayesian Kernel Inference (2024), addressing the challenge of reliable map construction in off-road settings where sensor data is inherently unreliable. His work consistently bridges perception, planning, and control, earning recognition for its practical relevance in defense and disaster response. With a career marked by high-impact, application-driven research, Min continues to shape how robots perceive and navigate the world’s most demanding terrains.