Towards Autonomous In-situ Soil Sampling and Mapping in Large-Scale Agricultural Environments

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Nguyen, Thien Hoang, Muller, Erik, Rubin, Michael, Wang, Xiaofei, Sibona, Fiorella, McBratney, Alex, Sukkarieh, Salah
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911156145225728
author Nguyen, Thien Hoang
Muller, Erik
Rubin, Michael
Wang, Xiaofei
Sibona, Fiorella
McBratney, Alex
Sukkarieh, Salah
author_facet Nguyen, Thien Hoang
Muller, Erik
Rubin, Michael
Wang, Xiaofei
Sibona, Fiorella
McBratney, Alex
Sukkarieh, Salah
contents Traditional soil sampling and analysis methods are labor-intensive, time-consuming, and limited in spatial resolution, making them unsuitable for large-scale precision agriculture. To address these limitations, we present a robotic solution for real-time sampling, analysis and mapping of key soil properties. Our system consists of two main sub-systems: a Sample Acquisition System (SAS) for precise, automated in-field soil sampling; and a Sample Analysis Lab (Lab) for real-time soil property analysis. The system's performance was validated through extensive field trials at a large-scale Australian farm. Experimental results show that the SAS can consistently acquire soil samples with a mass of 50g at a depth of 200mm, while the Lab can process each sample within 10 minutes to accurately measure pH and macronutrients. These results demonstrate the potential of the system to provide farmers with timely, data-driven insights for more efficient and sustainable soil management and fertilizer application.
format Preprint
id arxiv_https___arxiv_org_abs_2506_05653
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Towards Autonomous In-situ Soil Sampling and Mapping in Large-Scale Agricultural Environments
Nguyen, Thien Hoang
Muller, Erik
Rubin, Michael
Wang, Xiaofei
Sibona, Fiorella
McBratney, Alex
Sukkarieh, Salah
Robotics
Emerging Technologies
Traditional soil sampling and analysis methods are labor-intensive, time-consuming, and limited in spatial resolution, making them unsuitable for large-scale precision agriculture. To address these limitations, we present a robotic solution for real-time sampling, analysis and mapping of key soil properties. Our system consists of two main sub-systems: a Sample Acquisition System (SAS) for precise, automated in-field soil sampling; and a Sample Analysis Lab (Lab) for real-time soil property analysis. The system's performance was validated through extensive field trials at a large-scale Australian farm. Experimental results show that the SAS can consistently acquire soil samples with a mass of 50g at a depth of 200mm, while the Lab can process each sample within 10 minutes to accurately measure pH and macronutrients. These results demonstrate the potential of the system to provide farmers with timely, data-driven insights for more efficient and sustainable soil management and fertilizer application.
title Towards Autonomous In-situ Soil Sampling and Mapping in Large-Scale Agricultural Environments
topic Robotics
Emerging Technologies
url https://arxiv.org/abs/2506.05653