3D SENSING APPROACHES FOR PRECISION AGRICULTURE: APPLICATIONS TO PLANT FEATURES CHARACTERIZATION AND TO WEED CONTROL IN MAIZE
type: CreativeWork
description: This PhD thesis investigates the application of 3D data acquired by Time-of-Flight (ToF) sensors and stereo cameras for agronomic measurements. The main objectives are the characterization of plant geometric properties, biomass estimation with non-destructive methods and discrimination between crops and weeds for use in precision agriculture applications. Following an introductory section, the first part of the work, which corresponds to Chapters 3 and 4, involves the volumetric characterization of lettuce plants to estimate biomass using non-destructive measurements. This was performed both in preliminary laboratory trials and in a field application. In the field application the depth sensor was integrated with a robotic platform to ensure the possibility to collect data at the individual plant level, with all data that can be stored in a data lake. In both cases, the assumed volumetric reconstruction algorithms achieved very satisfactory results, obtaining accurate dry biomass weight (DM) estimates from the developed models for both laboratory scale (with a root mean square error (RMSE) of 0.12 g and a mean absolute percentage error (MAPE) of 12%.) and greenhouse conditions (with a RMSE of 1.07 g and MAPE 16%). The different ability to estimate the DM obtained in the two contexts, although minimal, depends mainly on the different spatial resolutions obtainable with the acquisition setups designed for the two experiments and on the conditions under which the measurements were carried out. Considering the technological characteristics of the ToF sensors, under field conditions they are disturbed by solar radiation, which contributes to decreasing the level of accuracy of the measurement obtained. The second part of the thesis, which corresponds to Chapters 5, 6, 7 and 8, deals with the comparison of two sensing techniques, two-dimensional based on color (RGB) and three-dimensional that consider distance in addition to color (RGBD) to optimize the process of target i…
abstract: This PhD thesis investigates the application of 3D data acquired by Time-of-Flight (ToF) sensors and stereo cameras for agronomic measurements. The main objectives are the characterization of plant geometric properties, biomass estimation with non-destructive methods and discrimination between crops and weeds for use in precision agriculture applications. Following an introductory section, the first part of the work, which corresponds to Chapters 3 and 4, involves the volumetric characterization of lettuce plants to estimate biomass using non-destructive measurements. This was performed both in preliminary laboratory trials and in a field application. In the field application the depth sensor was integrated with a robotic platform to ensure the possibility to collect data at the individual plant level, with all data that can be stored in a data lake. In both cases, the assumed volumetric reconstruction algorithms achieved very satisfactory results, obtaining accurate dry biomass weight (DM) estimates from the developed models for both laboratory scale (with a root mean square error (RMSE) of 0.12 g and a mean absolute percentage error (MAPE) of 12%.) and greenhouse conditions (with a RMSE of 1.07 g and MAPE 16%). The different ability to estimate the DM obtained in the two contexts, although minimal, depends mainly on the different spatial resolutions obtainable with the acquisition setups designed for the two experiments and on the conditions under which the measurements were carried out. Considering the technological characteristics of the ToF sensors, under field conditions they are disturbed by solar radiation, which contributes to decreasing the level of accuracy of the measurement obtained. The second part of the thesis, which corresponds to Chapters 5, 6, 7 and 8, deals with the comparison of two sensing techniques, two-dimensional based on color (RGB) and three-dimensional that consider distance in addition to color (RGBD) to optimize the process of target i…
author: TORRENTE, MARCO DAVIDE MICHEL
language: eng
keywords: Settore AGRI-04/B - Meccanica agraria
date published: 2024-12-16
date modified: 2026-07-27T20:19:08Z
provider: Università degli Studi di Milano
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Università degli Studi di Milano

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property ID: Handle
value: https://hdl.handle.net/2434/1119203