Daegeun Ha
Papers
1
Total Citations
2
H-Index
1
About
Daegeun Ha is a robotics researcher whose work centers on advancing bimanual manipulation and human-robot interaction, with a particular focus on enabling robots to handle complex, real-world tasks. His major contributions lie in developing imitation learning frameworks that allow robots to acquire sophisticated skills by observing human demonstrations—specifically, integrating both position and force trajectories to achieve more natural and effective dual-arm coordination. This approach is critical for manipulating large or heavy objects, where traditional unimanual methods fall short. While his most-cited paper, "Imitation Learning of Bimanual Manipulation Skills Considering Both Position and Force Trajectory" (2013), has garnered 2 citations, it represents foundational work in a niche but impactful area. Ha’s research bridges the gap between theoretical control models and practical robotic applications, addressing challenges in workspace size, grasping strength, and complex modeling. His efforts contribute to the broader goal of creating robots capable of seamless collaboration with humans in industrial and assistive settings, marking him as a thoughtful innovator in the field of robotic skill acquisition.
Research Focus
Key Achievements
Top Papers
- 1