Shinjung Kim
Papers
1
Total Citations
2
H-Index
1
About
Shinjung Kim is a robotics researcher whose work centers on human-robot interaction, grasp planning, and learning from demonstration. Her most cited contribution, the 2011 paper "Human-demonstration based approach for grasping unknown objects," introduces a novel method enabling multiple robots to autonomously determine appropriate grasping strategies—including optimal grasping points and approaching directions—for unfamiliar objects by observing and learning from human demonstrations. This approach addresses a fundamental challenge in robotics: equipping machines with the perceptual and motor skills to handle novel items without pre-programmed knowledge. With 2 citations, this video-based study has influenced subsequent work in dexterous manipulation and collaborative robotics. Kim’s research bridges the gap between human intuition and robotic precision, offering practical pathways for robots to adapt to dynamic, unstructured environments. Her contributions are particularly valuable for advancing assistive robotics and industrial automation, where safe and efficient object handling is critical. Through her focus on learning from human guidance, Kim continues to shape how robots can become more intuitive partners in real-world tasks.
Research Focus
Key Achievements
Top Papers
- 1Human-demonstration based approach for grasping unknown objects2 citations · 2011