Koenraad Vandevoorde

KU Leuven

Papers

1

Total Citations

147

H-Index

1

About

Koenraad Vandevoorde is a leading researcher in agricultural robotics and computer vision, with a primary focus on precision fruit harvesting. His most influential work centers on developing advanced sensing systems for automated fruit detection in orchards. In his landmark 2016 paper, "Detection of red and bicoloured apples on tree with an RGB-D camera," which has garnered 147 citations, Vandevoorde pioneered a method combining color and depth data to reliably identify apples under natural lighting conditions—a critical challenge for robotic harvesting. This contribution has significantly advanced the field of agricultural automation, enabling more efficient and selective fruit picking while reducing labor costs. Vandevoorde's research bridges the gap between computer vision algorithms and practical agricultural applications, demonstrating how RGB-D cameras can overcome occlusion and variable illumination issues in orchard environments. His work has been instrumental in moving robotic fruit harvesting from theoretical concepts toward commercial viability, and continues to influence subsequent studies in agricultural perception systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
147
Total Citations
147
Avg Citations/Paper
🏆 Most Cited Paper
Detection of red and bicoloured apples on tree with an RGB-D camera
147 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: KU Leuven

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago