Cabbage Detection and Positional Pose Estimation for Automated Harvesting

Abstract

In recent years, research has been conducted to automate various tasks in agriculture using robots and machinery. Harvesting incurs significant costs compared to other agricultural operations, with cabbage harvesting accounting for about 30% of the total. Therefore, cost reduction through automation is highly anticipated in this area. In this paper, we propose a method for estimating the position and orientation of cabbages to harvest them without causing damage. The position and orientation of cabbages can be determined by assuming that they are ellipsoids. In experiments comparing the position and orientation estimation using information obtained solely from an RGB-D camera and using point cloud information from a 3D LiDAR, for cabbages where the inner ball is minimally obstructed by outer leaves, both sensors yielded mostly favorable results with tilts of 20 degrees or less.