Masaki Suwa
Papers
1
Total Citations
2
H-Index
1
About
Masaki Suwa is a robotics and computer vision researcher whose work focuses on advancing intelligent automation systems for industrial applications. His research centers on the development of robust bin picking systems — a critical challenge in modern factory automation — with particular emphasis on overcoming the persistent difficulties posed by metallic objects, which often yield sparse and noisy three-dimensional data that confound conventional sensing approaches. Suwa's most notable contribution addresses this challenge through an innovative multi-view active vision framework that leverages a one-shot 3D sensor in a "sensor on hand" configuration. This non-stop, high-speed architecture delivers a compelling combination of cost-effectiveness, flexibility, and reliability, qualities that are essential for real-world industrial deployment. By enabling continuous, dynamic object recognition and manipulation even under challenging sensing conditions, his system represents a meaningful step forward in making robotic bin picking practical at scale. Though early in its citation trajectory — with 2 citations since its 2024 publication — this work has drawn attention from the automation community and reflects broader industry momentum toward smarter, more adaptable robotic systems. Suwa's research sits at an important intersection of robotics, 3D sensing, and manufacturing intelligence.
Research Focus
Key Achievements
Top Papers
- 1