Hiroki Imamura
Papers
4
Total Citations
19
H-Index
3
About
Hiroki Imamura’s research lies at the intersection of agricultural robotics and computer vision, with a focus on developing autonomous systems for hydroponic farming. His most cited work, “An Improvement of Positional Accuracy for View-Based Navigation Using SURF” (2010, 9 citations), introduced a reliable method for mobile robot navigation by leveraging feature-point extraction, significantly enhancing positional accuracy compared to traditional block-matching approaches. This foundational contribution underpins his later efforts to create a remote hydroponic management system, where robots must autonomously recognize and manage crops. Imamura’s key innovation is in robust fruit detection under occlusion—a critical challenge in real-world farms. His 2015 paper (4 citations) proposed a method combining hue information with curvature analysis to reliably identify mini tomatoes even when partially hidden, while a 2014 variant (2 citations) used edge shape for similar purposes. To make these systems accessible to non-expert users, he also developed a markerless augmented reality interface (2017, 4 citations) for remote farm management. Though his citation counts are modest, Imamura’s work represents a practical, step-by-step approach to integrating robotics into controlled-environment agriculture, addressing both technical accuracy and user interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4