Papers
13
Total Citations
84
H-Index
5
About
Hyeun Jeong Min is a robotics researcher whose work spans multi-robot systems, computer vision, autonomous navigation, and human-robot interaction. His most influential contributions lie in the domain of vision-based robot coordination, where he has pioneered algorithms enabling leader-follower formations under conditions of limited sensory information — work that has garnered 18 citations and demonstrated both stability and observability in constrained environments. Min has also made significant strides in multi-robot coverage problems, developing novel frameworks that optimize not only path efficiency but also the number of robots required — a departure from traditional fixed-fleet assumptions that earned 15 citations and reshaped thinking in coordinated search strategies. His methodological toolkit draws heavily on entropy-based segmentation, feature-based covariance matching, and Bayesian inference, allowing robots to robustly perceive and respond to dynamic environments. Early work on autonomous docking and behavior-network navigation established his foundation in intelligent mobile robotics, while more recent research on cooking robot systems demonstrates his expanding interest in practical, real-world human-facing applications, including food recognition and manipulation using instance segmentation. With a body of work accumulating citations across a decade and a half of publication, Min represents a versatile and steadily evolving voice in applied autonomous systems research.
Research Focus
Key Achievements
Top Papers
- 1Vision-based leader-follower formations with limited information18 citations · 2009
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- 3Robot Formations Using a Single Camera and Entropy-based Segmentation12 citations · 2012
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- 9Entropy-based motion segmentation from a moving platform3 citations · 2009
- 10Generating Homogeneous Map with Targets and Paths for Coordinated Search3 citations · 2018