David Rapado Rincon

David Rapado Rincon is a Research Associate and PhD candidate in Agricultural Biosystems Engineering at Wageningen University & Research, specializing in computer vision for agricultural robotics. His work focuses on developing advanced tracking systems for greenhouse automation, particularly for tomato plant analysis.

His research interests center on multi-object tracking in cluttered agricultural environments, with expertise in 3D pose estimation, semantic world modeling, and transformer-based vision systems. Key contributions include developing algorithms for detecting plant nodes and peduncles in tomato greenhouses using deep learning and multi-view vision systems.

Rapado Rincon's recent publications (2024-2025) reveal a strong trend toward real-time 3D tracking solutions for agro-food robotics, with emphasis on transformer architectures (MOT-DETR), next-best-view planning, and comparative analysis of single-stage versus two-stage tracking approaches. His work consistently addresses challenges in natural variation handling and sensor noise resilience within greenhouse environments.

He leads the active PhD project Semantic World Modeling for Agro-food Robotics (2020-present), supervised by Prof. E.J. van Henten and Dr. G. Kootstra, which integrates computer vision with robotic systems for plant part detection. His research has generated significant academic interest with multiple publications in high-impact journals including Computers and Electronics in Agriculture and Biosystems Engineering.

Rapado Rincon maintains an active research profile with 10 documented outputs (8 articles, 1 conference paper, 1 other contribution), including a dataset for 3D tomato peduncle pose estimation. His work shows strong industry relevance for agricultural automation, with collaborations focused on practical implementation in greenhouse robotics.