Vision-Based Perception for an Autonomous Harvester

Abstract

This paper describes a vision-based perception system which has been used to guide an automated harvester cutting fields of alfalfa hay. The system tracks the boundary between cut and uncut crop; indicates when the end of a crop row has been reached; and identifies obstacles in the harvester's path. The system adapts to local variations in lighting and crop conditions, and explicitly models and removes noise due to shadow. In field tests, the machine has successfully operated in four different locations, at sites in Pennsylvania, Kansas, and California. Using the vision system as the sole means of guidance, over 60 acres have been cut at speeds of up to 4.5 mph (typical human operating speeds range from 3-6 mph). Future work largely centers around combining vision and GPS based navigation techniques to produce a commercially viable product for use either as a navigation aid or for a completely autonomous system.