Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Design and Evaluation of a UGV-Based Robotic Platform for Precision Soil Moisture Remote Sensing

Ilektra Tsimpidi, Ilias Tevetzidis, Vidya Sumathy, George Nikolakopoulos

TL;DR

Enables autonomous, high-precision soil moisture sensing in large agricultural fields using the AgriOne UGV equipped with a TEROS 12 sensor on a robotic manipulator. The core method combines a robust robotic platform with a surface aware data collection framework that discards invalid measurements and converts raw sensor outputs to volumetric water content via $ \theta (m^{3}/m^{-3}) = 3.879 \times 10^{-4} \times RAW - 0.6956 $. Field tests in open terrain demonstrated reliable, real-time data acquisition across ~380 m² with 70 valid points, reducing the need for permanent sensors. The work advances precision agriculture by delivering autonomous, cost-efficient soil moisture mapping and highlights directions for automated point selection and geographic feature-based VWC modeling.

Abstract

This extended abstract presents the design and evaluation of AgriOne, an automated unmanned ground vehicle (UGV) platform for high precision sensing of soil moisture in large agricultural fields. The developed robotic system is equipped with a volumetric water content (VWC) sensor mounted on a robotic manipulator and utilizes a surface-aware data collection framework to ensure accurate measurements in heterogeneous terrains. The framework identifies and removes invalid data points where the sensor fails to penetrate the soil, ensuring data reliability. Multiple field experiments were conducted to validate the platform's performance, while the obtained results demonstrate the efficacy of the AgriOne robot in real-time data acquisition, reducing the need for permanent sensors and labor-intensive methods.

Design and Evaluation of a UGV-Based Robotic Platform for Precision Soil Moisture Remote Sensing

TL;DR

Enables autonomous, high-precision soil moisture sensing in large agricultural fields using the AgriOne UGV equipped with a TEROS 12 sensor on a robotic manipulator. The core method combines a robust robotic platform with a surface aware data collection framework that discards invalid measurements and converts raw sensor outputs to volumetric water content via . Field tests in open terrain demonstrated reliable, real-time data acquisition across ~380 m² with 70 valid points, reducing the need for permanent sensors. The work advances precision agriculture by delivering autonomous, cost-efficient soil moisture mapping and highlights directions for automated point selection and geographic feature-based VWC modeling.

Abstract

This extended abstract presents the design and evaluation of AgriOne, an automated unmanned ground vehicle (UGV) platform for high precision sensing of soil moisture in large agricultural fields. The developed robotic system is equipped with a volumetric water content (VWC) sensor mounted on a robotic manipulator and utilizes a surface-aware data collection framework to ensure accurate measurements in heterogeneous terrains. The framework identifies and removes invalid data points where the sensor fails to penetrate the soil, ensuring data reliability. Multiple field experiments were conducted to validate the platform's performance, while the obtained results demonstrate the efficacy of the AgriOne robot in real-time data acquisition, reducing the need for permanent sensors and labor-intensive methods.

Paper Structure

This paper contains 7 sections, 1 equation, 4 figures.

Table of Contents

  1. INTRODUCTION
  2. METHODOLOGY
  3. Design of the robotic platform - AgriOne
  4. Surface aware data collection framework
  5. Field Experiment
  6. RESULTS
  7. Conclusion

Figures (4)

  • Figure 1: AgriOne robot integrated with Meter TEROS 12 soil sensor used for soil moisture measurement and the schematic view of the linear actuator probe.
  • Figure 2: The flowchart depicting the surface aware data collection framework algorithm, based on which AgriOne robot measure and collect soil moisture data.
  • Figure 3: (a) Front-view (b) Side-view of the AgriOne robot during soil moisture measurement experiments
  • Figure 4: Experiment results: (a) Satellite imagery of the experiment area and the data collection points along the robots's trajectory (b) spatial distribution of soil moisture across the geographic area based on the collected data samples.