Papers
4
Total Citations
23
H-Index
3
About
Minho Oh is a roboticist advancing autonomous navigation in the most challenging, unstructured environments—from mountain trails and caves to disaster zones and construction sites. His core research centers on traversability estimation, ground segmentation, and safe path planning for legged and terrestrial robots operating where traditional approaches fail. Oh’s most cited work, “TRG-Planner” (2025, 10 citations), introduces a Traversal Risk Graph that enables robots to plan paths that avoid hazardous terrain while balancing speed and safety, a critical capability for real-world deployment. His comprehensive survey on ground segmentation and traversability estimation (2024, 7 citations) has become a key reference for researchers tackling similar problems. Oh also developed TOSS (2024), a real-time tracking and moving object segmentation system for static scene mapping, and BIG-STEP (2023), a robust state estimator for legged robots that achieves fast, reliable ground segmentation. Together, these contributions demonstrate Oh’s commitment to making robots not just autonomous, but truly capable in the wild—where every step matters.
Research Focus
Key Achievements
Top Papers
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