Takuya Ikai
Papers
5
Total Citations
32
H-Index
3
About
Takuya Ikai is a robotics researcher focused on bridging the gap between human intention and machine action through multimodal sensing. His work centers on developing intuitive human-robot interaction systems that combine vision and tactile feedback, enabling robots to understand natural human instructions without requiring specialized programming. Ikai's major contributions include pioneering finger direction recognition methods that allow robots to interpret pointing gestures in 3D space using stereo vision, as well as systems that integrate optical three-axis tactile sensors with binocular vision for precise object manipulation and edge extraction. His research on robot control via visual and tactile sensations, which has accumulated 15 citations, demonstrates how spontaneous human movements can be translated into effective robot commands for daily life assistance. Ikai has also explored how robots can extract geometrical data from objects through physical interaction, mimicking human exploratory behaviors like pushing and pulling. His work on stress-free human-robot collaboration has significant implications for assistive robotics and industrial automation, where natural communication between humans and machines is essential for safe, efficient operation in shared workspaces.
Research Focus
Key Achievements
Top Papers
- 1Robot Control Using Natural Instructions Via Visual and Tactile Sensations15 citations · 2016
- 2
- 3Edge Extraction using Image and Three-Axis Tactile Data6 citations · 2011
- 4Behavior Control of Robot by Human Finger Direction3 citations · 2012
- 5