Papers
3
Total Citations
62
H-Index
3
About
Romain Chapuis is a researcher whose work bridges the fields of robotics, sensor fusion, and agricultural technology. His primary research areas include real-time multi-sensor data fusion, autonomous vehicle localization, and high-throughput phenotyping for plant breeding. Chapuis made a significant early contribution with his development of the AROCCAM software architecture, a real-time framework designed to integrate delayed observations from multiple unsynchronized sensors. This work, published in 2006 and cited 37 times, provided a practical solution for building complex data fusion applications, particularly for vehicle localization. He further advanced localization systems by addressing GNSS bias correction for low-cost sensors in autonomous mobile robot guidance. More recently, Chapuis has applied his expertise to the pressing challenge of climate-resilient agriculture. His 2023 paper, cited 21 times, demonstrates how robotized indoor phenotyping can enable genomic prediction of adaptive traits like plant architecture and stomatal conductance, traits crucial for breeding crops that can withstand changing environmental conditions. This work challenges the assumption that indoor phenotyping lacks field relevance, showcasing its potential for speed breeding and securing future food production.
Research Focus
Key Achievements
Top Papers
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- 3GNSS Bias Correction for localization systems4 citations · 2008