Authors:

Martin Vassilev

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About Paper:

With global populations rapidly rising, the need for robotic automation in precision agriculture has become increasingly important. Integrating automated technologies is necessary to optimize resource use and minimize environmental impact. Soil moisture sensing is shown to be a powerful tool for monitoring moisture levels, allowing for optimized irrigation of crops and increased yield. However, challenges such as accurate sensor deployment, reliable sensor reading, and robust navigation in variable field conditions have limited the widespread adoption of such systems. This work introduces the development of Purdue-AgBot (P-AgBot), an unmanned ground vehicle (UGV) that autonomously deploys and reads IoT4Ag biodegradable soil moisture sensors. This research aims to achieve over 90% precision in sensor deployment and to improve the reliability of sensor readings, with a goal of exceeding 95% successful data retrieval. The project aims to reduce the average time for each sensor reading cycle to under 2 minutes. Advancements include autonomous navigation through the integration of ArUco markers for visual servoing, upgrades to the P-AgBot's electronics, and refinement of the sensor deployment system. These approaches have been experimentally verified with simulations as well as bi-weekly deployment in-field over a period of two months. Soil moisture sensors were shown to be autonomously deployed and read using the P-AgBot. The results of this research demonstrate the feasibility of scalable, automated soil monitoring, which has the potential to enhance water conservation and crop yields in precision agriculture. Future work will focus on expanding the system's capabilities to additional sensor types and further improving operational efficiency. Keywords: Precision Agriculture; Robotic Automation; Soil Moisture Sensing; Sensor Deployment; Autonomous Navigation

Source:

Purdue University / 2025

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Co-authors:

Martin Vassilev