Yong-Hyun Jo
Papers
1
Total Citations
4
H-Index
1
About
Yong-Hyun Jo is a robotics researcher whose work centers on 3D mapping and spatial perception for autonomous systems, with a particular focus on enabling real-time environmental understanding for mobile robots. His most-cited paper, "Memory-efficient real-time map building using octree of planes and points" (2013, 4 citations), introduces an innovative octree-based mapping algorithm designed for home-service robots equipped with time-of-flight cameras. This contribution addresses a critical challenge in robotics: how to incrementally construct detailed 3D maps from successive point cloud data while maintaining computational efficiency and memory constraints. By representing environments as a hybrid structure of planes and points, Jo's approach allows robots to navigate and understand their surroundings in real time—a fundamental requirement for practical domestic applications. While his citation count remains modest, the work demonstrates a thoughtful engineering approach to balancing accuracy, speed, and resource usage in spatial mapping. Jo's research sits at the intersection of computer vision, sensor fusion, and embedded systems, contributing to the broader goal of making autonomous robots more capable and affordable for everyday environments. His work offers valuable insights for researchers developing perception systems for service robotics.
Research Focus
Key Achievements
Top Papers
- 1