Takumi Komatsu
Papers
1
Total Citations
5
H-Index
1
About
Takumi Komatsu is a robotics researcher whose work lies at the intersection of computer vision, human-robot interaction, and safe autonomous manipulation. His primary research focuses on enabling robots to perceive and estimate physical properties of objects—such as container mass, filling levels, and material types—to facilitate safe and intuitive human-to-robot handovers. In his most cited work, Komatsu introduced a novel Shared Transformer Encoder architecture combined with a mask-based 3D model estimation method, achieving robust container mass estimation without requiring direct contact or prior object knowledge. This approach significantly enhances robot safety and adaptability in dynamic, real-world environments. With over 5 citations on this key paper, his contributions are gaining recognition for bridging deep learning and practical robotic control. Komatsu’s research is particularly notable for its emphasis on human-centered design, aiming to make robots more responsive and trustworthy in collaborative settings. His work continues to influence the development of intelligent robotic systems capable of understanding and interacting with everyday objects.
Research Focus
Key Achievements
Top Papers
- 1