Papers
2
Total Citations
14
H-Index
2
About
Minsung Yoon is an emerging robotics researcher whose work sits at the intersection of autonomous navigation, legged locomotion, and machine learning-based control. His research focuses on equipping robots with the adaptive intelligence needed to operate reliably in real-world, unpredictable environments — a challenge that demands both perceptual robustness and dynamic physical stability. Yoon's most recognized contribution, "Confidence-Based Robot Navigation Under Sensor Occlusion with Deep Reinforcement Learning" (2022, 12 citations), addresses a critical practical problem in autonomous navigation: how robots can maintain safe, purposeful movement when sensors are physically compromised by dust, smudges, or soiling. By integrating confidence estimation into a deep reinforcement learning framework, his approach enables robots to reason about uncertainty and adapt their behavior accordingly — a meaningful step toward deployment in uncontrolled environments. His more recent work on quadruped robots tackles the formidable challenge of balancing on dynamic moving platforms such as buses, subways, and yachts, where unpredictable inertial forces demand continuous adaptive control. Though early in its citation trajectory, this research reflects a broader vision of versatile, real-world-ready legged robots. Yoon's portfolio signals a researcher steadily building foundational contributions to resilient, intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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