Field Robot for High-throughput and High-resolution 3D Plant Phenotyping

Autor:	Esser, Felix, Rosu, Radu Alexandru, Cornelißen, André, Klingbeil, Lasse, Kuhlmann, Heiner, Behnke, Sven
Rok vydání:	2023
Předmět:	Computer Science - Robotics
Druh dokumentu:	Working Paper
DOI:	10.1109/MRA.2023.3321402
Popis:	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. Comment: Accepted for IEEE Robotics and Automation Magazine
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2310.11516 Zobrazit plný text záznamu View this record from Arxiv