Hiroaki Masuzawa
Papers
12
Total Citations
144
H-Index
7
About
Hiroaki Masuzawa is a leading researcher in agricultural robotics, specializing in mobile robot navigation and scene understanding for greenhouse horticulture. His work addresses critical labor shortages in agriculture by developing autonomous systems capable of person following, 3D semantic mapping, and robust object recognition in plant-rich environments. Masuzawa’s major contributions include pioneering methods for traversable plant detection and manual annotation-free training of semantic segmentation models, enabling robots to navigate dense foliage without human intervention. His most cited paper, “Development of a mobile robot for harvest support in greenhouse horticulture” (2017, 35 citations), established foundational techniques for person following and mapping. Subsequent works, such as “3D Semantic Mapping in Greenhouses” (2018, 23 citations) and “Image-Based Scene Recognition” (2022, 20 citations), advanced robot path planning by integrating semantic information and deep learning. Notably, his research on multi-source pseudo-label learning (2022) and end-to-end path estimation (2023) demonstrates a commitment to scalable, data-efficient solutions. With over 130 total citations, Masuzawa’s innovations are shaping the future of precision agriculture, making him a key figure in the intersection of robotics, computer vision, and sustainable farming.
Research Focus
Key Achievements
Top Papers
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- 4Development of a Person Following Robot and Its Experimental Evaluation13 citations · 2010
- 5Observation planning for efficient environment information summarization12 citations · 2009
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