ARTIFICIAL LANDMARK SELF-LOCALIZATION FOR AGRICULTURAL VEHICLE FIELD ROAD NAVIGATION USING OMNIDIRECTIONAL VISION
This paper introduces an artificial landmark self-localization method using omnidirectional vision for agricultural vehicles field road navigation. We propose a landmark model and the algorithm to track landmark and calculate the absolute location of camera based on omnidirectional image. Red and blue landmark pixels beyond the threshold were extracted as a small area and the center of gravity of the extracted small area was calculated representing the landmark position candidates. The distance between landmark and camera in the image was estimated and transformed the image distance to spatial distance using distance computational model. The absolute location of camera was calculated by circle theorems. Outdoor experiments were conducted on a flat asphalt road in the field under natural sunlight. Experimental results showed that the RMS and mean distance errors are less than 24 cm in a 20 m distance. The self-localization method is feasible.
agricultural vehicle navigation omnidirectional vision localization