Brett Whelan

Australian Centre for Robotic Vision, The University of Sydney

Papers

Total Citations

309

H-Index

About

Brett Whelan is a leading researcher in precision agriculture and agricultural robotics, whose work bridges the gap between sensor technology and practical farm management. His key research areas include high-resolution crop sensing, 3D point cloud analysis, and autonomous field robotics for yield estimation and crop monitoring. Whelan’s major contributions center on developing non-destructive methods to quantify crop traits, such as using lidar and vision sensors to map almond orchard canopy volume, flowers, fruit, and yield—a study that has garnered 179 citations. He also pioneered techniques for segmenting lettuce in coloured 3D point clouds to estimate fresh weight (68 citations), enabling more precise harvesting and resource allocation. Notably, Whelan was instrumental in creating the high-resolution, multimodal “Ladybird’s-eye view” data set for Brassica crops (62 citations), collected by the autonomous field robot Ladybird at the Australian Centre for Field Robotics. This open-access resource, covering weekly scans of cauliflower and broccoli over a full growth cycle, has become a benchmark for agricultural robotics research. Whelan’s work has profoundly impacted the shift toward data-driven, automated farming, making him a key figure in the global precision agriculture community.