  We propose a geometry-based grasping method for vine tomatoes. It relies on a
computer-vision pipeline to identify the required geometric features of the
tomatoes and of the truss stem. The grasping method then uses a geometric model
of the robotic hand and the truss to determine a suitable grasping location on
the stem. This approach allows for grasping tomato trusses without requiring
delicate contact sensors or complex mechanistic models and under minimal risk
of damaging the tomatoes. Lab experiments were conducted to validate the
proposed methods, using an RGB-D camera and a low-cost robotic manipulator. The
success rate was 83% to 92%, depending on the type of truss.
