3D Skeletonization of Complex Grapevines for Robotic Pruning
Eric Schneider Sushanth Jayanth Abhisesh Silwal George Kantor
Robotic pruning of dormant grapevines is an area of active research in order
to promote vine balance and grape quality, but so far robotic efforts have
largely focused on planar, simplified vines not representative of commercial
vineyards. This paper aims to advance the robotic perception capabilities
necessary for pruning in denser and more complex vine structures by extending
plant skeletonization techniques. The proposed pipeline generates skeletal
grapevine models that have lower reprojection error and higher connectivity
than baseline algorithms. We also show how 3D and skeletal information enables
prediction accuracy of pruning weight for dense vines surpassing prior work,
where pruning weight is an important vine metric influencing pruning site
selection.