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