Towards Autonomous In-situ Soil Sampling and Mapping in Large-Scale Agricultural Environments
Thien Hoang Nguyen, Erik Muller, Michael Rubin, Xiaofei Wang, Fiorella Sibona, Alex McBratney, and Salah Sukkarieh

TL;DR
This paper introduces a robotic system for real-time, in-situ soil sampling and analysis in large-scale agriculture, enabling precise, timely soil property mapping to improve farm management.
Contribution
The paper presents a novel integrated robotic system combining automated soil sampling and rapid analysis, validated through extensive field trials in a large-scale agricultural setting.
Findings
System can acquire 50g soil samples at 200mm depth
Samples are analyzed within 10 minutes for key properties
System provides timely data for sustainable soil management
Abstract
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…
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Taxonomy
TopicsSoil Geostatistics and Mapping · Smart Agriculture and AI · Soil Mechanics and Vehicle Dynamics
