Papers
25
Total Citations
555
H-Index
9
About
Takuya Kiyokawa is a robotics researcher whose work spans human-robot collaboration, robotic manipulation, waste sorting automation, and assembly planning. His most influential contribution—a 2022 systematic review on quality metrics in human-robot interaction (257 citations)—has become a foundational reference for researchers and practitioners navigating the emerging Industry 5.0 landscape, offering a rigorous classification of performance and human-centered evaluation frameworks. Kiyokawa has made substantial strides in sustainable robotics, addressing the urgent global challenge of waste management through intelligent robotic sorters capable of recognizing and manipulating mixed industrial waste, work that has attracted significant scholarly attention. His research on assembly sequence planning demonstrates a commitment to reducing human teaching burden in industrial automation, leveraging 3D CAD models and genetic algorithms to generate efficient, robot-executable sequences—including for products with deformable parts. Kiyokawa also explores cutting-edge sensing modalities, such as visuotactile in-hand pose estimation, and environmental robotics, including UAV-UUV systems for marine debris collection. Across more than 400 cumulative citations, his body of work reflects a researcher deeply engaged in making robots more capable, collaborative, and socially responsible partners in complex real-world environments.
Research Focus
Key Achievements
Top Papers
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- 2Challenges for Future Robotic Sorters of Mixed Industrial Waste: A Survey57 citations · 2022
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- 4Robotic Waste Sorter with Agile Manipulation and Quickly Trainable Detector33 citations · 2021
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