Kyu-Ho Sim
Papers
2
Total Citations
7
H-Index
2
About
Kyu-Ho Sim’s research focuses on intelligent robotics, specifically the integration of computer vision and machine learning for autonomous manipulation and navigation. His work addresses critical challenges in service robotics, from household assistance to industrial precision. In a foundational 2011 study (4 citations), Sim developed an intelligent vision system enabling indoor service robots to perform object localization and obstacle avoidance—key capabilities for tasks like cleaning and vacuuming. This early work laid the groundwork for more advanced contributions. By 2019, Sim advanced the field with a novel approach combining two different CNN algorithms for object detection and robotic grasping control (3 citations). Rather than predicting individual parameters, his method holistically determines an object’s center coordinates, width, and yaw angle, enabling more precise and reliable grasping. This work directly impacts the development of dexterous robot manipulators for manufacturing and service applications. While his citation counts are modest, Sim’s research represents a clear progression from basic vision-based navigation to sophisticated deep-learning-driven manipulation, demonstrating a sustained commitment to solving real-world robotics problems. His work is particularly relevant for researchers exploring the intersection of computer vision, deep learning, and robotic control.
Research Focus
Key Achievements
Top Papers
- 1
- 2