Changhyun Jun
Papers
4
Total Citations
33
H-Index
3
About
Changhyun Jun is a robotics researcher whose work centers on practical robotic manipulation, automated construction assessment, and simultaneous localization and mapping (SLAM). His most influential contribution is the "Minimal Grasper," a flexible, self-adaptive robotic hand designed for pick-and-place tasks. This grasper, detailed in his most-cited paper (17 citations), achieves robust performance with low task planning complexity, making it highly suitable for real-world industrial applications. Jun also developed an adjusted benefit-cost analysis model for evaluating the economic efficiency of robot-based automated construction systems, moving beyond traditional monetary comparisons. In the SLAM domain, he has analyzed reference coordinate system effects in EKF-based frameworks and contributed to object-oriented 3D RGB-D mapping for realistic indoor world reconstruction. With a total of 33 citations across his key works, Jun’s research bridges practical hardware design and algorithmic mapping, offering accessible solutions for automation and spatial understanding. His work is particularly valuable for students and researchers interested in low-complexity grasping systems and the integration of economic assessment with robotics.
Research Focus
Key Achievements
Top Papers
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- 3Analysis of the reference coordinate system used in the EKF-based SLAM5 citations · 2014
- 4