Cheol-Hong Min

University of St. Thomas - Minnesota, Seoul National University

Papers

Total Citations

H-Index

About

Cheol-Hong Min is a researcher at the forefront of embodied AI and precision agriculture, bridging the gap between autonomous systems and real-world applications. His work centers on developing intelligent robotic systems that perceive and act within complex environments. A key contribution is his leadership in creating ReALFRED (2024), a benchmark for embodied instruction following in photo-realistic settings. This work pushes the boundaries of how robots understand and execute human commands in visually rich, dynamic spaces, establishing a critical standard for the field. Earlier, Min made significant strides in precision agriculture with his 2018 paper on automatic crop furrow detection, which proposed a machine vision system for crop row and weed identification—a foundational step toward fully automated farming. While his citation counts are still growing (5 and 3 citations respectively), the novelty and timeliness of his research signal strong potential for future impact. Min’s work exemplifies a commitment to solving tangible problems through cutting-edge AI, making him a notable figure in the evolution of autonomous, perception-driven robotics.