Variable field-of-view machine vision based row guidance of an agricultural robot

A novel variable field-of-view machine vision method was developed allowing an agricultural robot to navigate between rows in cornfields. The machine vision hardware consisted of a camera with pitch and yaw motion control. Guidance lines were detected using an image-processing algorithm, employing morphological features in a far, near and lateral field of view, and the robot was guided along these lines using fuzzy logic control.The method was tested while the vehicle successfully traveled through a distance of 30 m towards the end of a crop row in three replications. To evaluate the guidance performance, RTK-GPS data were collected, showing a maximum guidance error of 15.8 mm and stable navigational behavior.

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► A robot was guided using a camera in a near, far and lateral field of view (FOV) mode.
► The control of the robot was implemented using a fuzzy logic algorithm.
► The far FOV had the best performance, and the near FOV had the worst performance.
► All three methods had acceptable accuracy since the worst-case guidance error was 15.8 mm.