AUTOMATED AGRICULTURAL EQUIPMENT NAVIGATION USING STEREO DISPARITY IMAGES

摘要

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.