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In this paper we propose a robotic system for Irrigation Water Management(IWM) in a structured robotic greenhouse environment. A commercially availablerobotic manipulator is equipped with an RGB-D camera and a soil moisturesensor. The two are used to automate the procedure known as "feel andappearance method", which is a way of monitoring soil moisture to determinewhen to irrigate and how much water to apply. We develop a compliant forcecontrol framework that enables the robot to insert the soil moisture sensor inthe sensitive plant root zone of the soil, without harming the plant. RGB-Dcamera is used to roughly estimate the soil surface, in order to plan the soilsampling approach. Used together with the developed adaptive force controlalgorithm, the camera enables the robot to sample the soil without knowing theexact soil stiffness a priori. Finally, we postulate a deep learning basedapproach to utilize the camera to visually assess the soil health and moisturecontent.

Robotic Irrigation Water Management: Estimating Soil Moisture Content by Feel and Appearance