Using multiple sensors to detect uncut crop edges for autonomous guidance systems of head-feeding combine harvesters

Abstract

This study proposes a method for detection of uncut crop edges using multiple sensors to provide accurate data for the autonomous guidance systems of head-feeding combine harvesters widely used in the paddy fields of Japan for harvesting rice. The proposed method utilizes navigation sensors, such as a real-time kinematic global positioning system (RTK-GPS), GPS compass, and laser range finder (LRF), to generate a three-dimensional map of the terrain to be harvested at a processing speed of 35 ms and obtain the crop height. Furthermore, it can simultaneously detect the uncut crop edges by RANdom SAmple Consensus (RANSAC). The average of the lateral offset value and crop height of the uncut crop edge detected by the proposed method were 0.154 m and 0.537 m, respectively.