  With the need to feed a growing world population, the efficiency of crop
production is of paramount importance. To support breeding and field
management, various characteristics of the plant phenotype need to be measured
-- a time-consuming process when performed manually. We present a robotic
platform equipped with multiple laser and camera sensors for high-throughput,
high-resolution in-field plant scanning. We create digital twins of the plants
through 3D reconstruction. This allows the estimation of phenotypic traits such
as leaf area, leaf angle, and plant height. We validate our system on a real
field, where we reconstruct accurate point clouds and meshes of sugar beet,
soybean, and maize.
