On the Intelligent Control Design of an Agricultural Mobile Robot for Cotton Crop Monitoring

In this work, we address the modelling and control design of a wheeled mobile robot capable of performing autonomous navigation tasks in agricultural fields. The methodology is based on the kinematics approach due to its wellknown ability to ensure satisfactory performance when the robot motions are carried out with low velocities and slow accelerations. Two control strategies are used for stabilization and trajectory tracking purposes: the first scheme is based on a fuzzy logic algorithm and considers the regulation problem of the robot position in Cartesian space; the second scheme is based on a visual servoing algorithm and considers the tracking problem of a straight line by using a constant linear velocity in Cartesian space and the position error in image space. Simulation results are presented to illustrate the effectiveness and feasibility of the fuzzy logic approach. Experimental tests with an agricultural mobile robot are carried out to verify and validate the visual servoing approach for cotton crop monitoring.