Liesbet Van Herck

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About

Liesbet Van Herck is a pioneering researcher in agricultural robotics, with a primary focus on advancing robotic harvesting systems for specialty crops. Her work centers on the intersection of computer vision, crop phenotyping, and mechanical design to enable selective, automated harvesting of fruits like sweet peppers. Van Herck’s most influential contribution is her 2020 study, “Crop design for improved robotic harvesting: A case study of sweet pepper harvesting,” which has garnered 30 citations and provides foundational insights into how crop architecture can be optimized for machine picking. She also developed innovative methods for maturity evaluation using multiple viewpoint color analyses (2016), addressing the critical challenge of limited fruit visibility—sweet peppers are only 65% visible from a single angle—and demonstrating that multiple camera perspectives can detect over 90% of harvest-ready fruit. Her work directly tackles the bottleneck of selective harvesting in greenhouse environments, combining agronomic principles with engineering solutions. Van Herck’s research is instrumental for students and engineers seeking to bridge the gap between plant breeding and automation, offering practical frameworks for designing crops that are both productive and robot-friendly.