N. Shibuya
Papers
3
Total Citations
8
H-Index
2
About
N. Shibuya’s research centers on mobile robotics, with a particular focus on self-localization and intuitive human-robot interaction. Shibuya pioneered a computationally efficient method for robot self-localization by compressing image data into statistical summaries—specifically, the average and standard deviation of pixel intensities per column. This approach, detailed in their most-cited work (2006, 4 citations), enables a robot to match compressed environmental data against observations, reducing processing demands while maintaining localization accuracy. A related study (2006, 2 citations) further validated this technique. In earlier work (2003, 2 citations), Shibuya explored practical home robot operation by combining a laser pointer interface with speech recognition, aiming to create a more natural and accessible control system. Though citation counts are modest, Shibuya’s contributions are notable for their emphasis on simplicity and real-world applicability—stripping away computational complexity to make autonomous navigation and user-friendly control more attainable. Their research offers valuable insights for students and engineers developing cost-effective, efficient robotic systems for domestic or constrained environments.
Research Focus
Key Achievements
Top Papers
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