AUTOMATED AGRICULTURAL EQUIPMENT NAVIGATION USING STEREO DISPARITY IMAGES
Visual perception is a key source of information for autonomous navigation of agricultural equipment. 
Stereoscopic vision improves the monocular vision by adding the third dimension (depth) to attain more accurate object 
localization within the sensed scene. This research used a compact stereovision camera to find paths from structured 
agricultural fields to automatically navigate a tractor following crop rows in the field. Stereo disparity was obtained by 
processing the stereo images of the structured crops. A linear regression method was applied to determine the position of the 
crop rows from the acquired stereo disparity. A base rule was developed to determine a central path for the tractor based on 
the resulting crop lines in a window of the interested region within the stereo disparity image. A target point was identified 
on the central path through stereo analysis, providing critical navigation information. This research proved that stereovision 
has a great potential for generating navigation information for autonomous agricultural tractors operating in a wide variety 
of field conditions.