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Soil apparent electrical conductivity (ECa) is a vital metric in PrecisionAgriculture and Smart Farming, as it is used for optimal water contentmanagement, geological mapping, and yield prediction. Several existing methodsseeking to estimate soil electrical conductivity are available, includingphysical soil sampling, ground sensor installation and monitoring, and the useof sensors that can obtain proximal ECa estimates. However, such methods can beeither very laborious and/or too costly for practical use over larger fieldcanopies. Robot-assisted ECa measurements, in contrast, may offer a scalableand cost-effective solution. In this work, we present one such solution thatinvolves a ground mobile robot equipped with a customized and adjustableplatform to hold an Electromagnetic Induction (EMI) sensor to performsemi-autonomous and on-demand ECa measurements under various field conditions.The platform is designed to be easily re-configurable in terms of sensorplacement; results from testing for traversability and robot-to-sensorinterference across multiple case studies help establish appropriate tradeoffsfor sensor placement. Further, a developed simulation software package enablesrapid and accessible estimation of terrain traversability in relation todesired EMI sensor placement. Extensive experimental evaluation acrossdifferent fields demonstrates that the obtained robot-assisted ECa measurementsare of high linearity compared with the ground truth (data collected manuallyby a handheld EMI sensor) by scoring more than $90\%$ in Pearson correlationcoefficient in both plot measurements and estimated ECa maps generated bykriging interpolation. The proposed robotic solution supports autonomousbehavior development in the field since it utilizes the ROS navigation stackalong with the RTK GNSS positioning data and features various ranging sensors.

Robot-assisted Soil Apparent Electrical Conductivity Measurements in Orchards