Kaname Narukawa
Papers
1
Total Citations
23
H-Index
1
About
Kaname Narukawa is a leading researcher in humanoid robotics, with a primary focus on real-time collision detection and safe autonomous movement. His most influential work introduces a novel collision detection method using one-class support vector machines (SVM), which enables humanoid robots to identify potential collisions using only normal movement data—eliminating the need for hazardous collision datasets. This approach significantly enhances robot safety during dynamic interactions with humans and environments. With his top-cited paper accumulating 23 citations, Narukawa’s contributions are foundational to the development of more adaptive and risk-aware robotic systems. His research bridges machine learning and robotics, offering practical solutions for real-time safety in complex settings. By prioritizing data efficiency and computational speed, Narukawa has advanced the field toward more intelligent, collision-free humanoid locomotion, making his work essential for researchers aiming to integrate robust safety mechanisms into next-generation autonomous robots.
Research Focus
Key Achievements
Top Papers
- 1