Moohyun Cha

Korea Institute of Machinery & Materials

Papers

Total Citations

H-Index

About

Moohyun Cha is a robotics researcher whose work centers on autonomous mobile robot navigation and control, with a particular focus on perception and manipulation in unstructured environments. His major contributions include developing an integrative tracking control strategy for robotic excavation, a key advancement for construction automation that addresses the complex dynamics of digging tasks. Cha’s research also tackles critical safety challenges in urban robotics, as demonstrated by his work on LiDAR-based detection of down-curbs and up-curbs—a vital capability for sidewalk- and road-navigating delivery robots. His most-cited paper, "Integrative Tracking Control Strategy for Robotic Excavation" (2021), has garnered 15 citations, reflecting its relevance to the growing field of autonomous heavy machinery. By addressing both the precision control of excavation and the perceptual hurdles of curb detection, Cha’s work bridges the gap between industrial robotics and last-mile delivery systems. His findings are particularly impactful for researchers developing robots that must operate reliably on paved, structured surfaces while avoiding common obstacles, making his contributions essential for advancing practical, real-world autonomy.