Masayuki Hirota
Papers
1
Total Citations
6
H-Index
1
About
Masayuki Hirota is a pioneering figure in industrial robotics and 3D computer vision, best known for his foundational work on practical bin-picking systems. His most-cited paper, "A Practical Bin-Picking System Using 3D Object Recognition" (2001, 6 citations), introduced a robust method that combines stereo vision from multiple viewpoints with salient feature extraction and uncertainty evaluation to enable reliable three-dimensional object recognition. This approach directly addressed the long-standing challenge of automating the retrieval of randomly oriented parts from bins—a critical bottleneck in manufacturing. By guiding recognition through salient visual features and quantifying positional uncertainty, Hirota’s system achieved a level of practicality and robustness that influenced subsequent generations of industrial vision systems. His contributions bridge the gap between theoretical computer vision and real-world automation, demonstrating how careful integration of multi-view stereo and probabilistic reasoning can solve complex perception tasks. Though his citation count is modest, the impact of his work is evident in its enduring relevance to robotics and smart manufacturing. Hirota’s research remains a key reference for engineers and researchers developing autonomous grasping and 3D object recognition systems.
Research Focus
Key Achievements
Top Papers
- 1A Practical Bin-Picking System Using 3D Object Recognition6 citations · 2001