A Sensor Fusion-based Cutting Device Attitude Control to Improve the Accuracy of Korean Cabbage Harvesting

TL;DR

This paper presents a sensor fusion-based attitude control system for Korean cabbage harvesters, aiming to improve harvesting accuracy on slopes by maintaining the cutting device's level and angle, validated through field tests.

Contribution

It introduces a novel attitude control mechanism using sensor fusion and hydraulic cylinders, specifically designed for Korean cabbage harvesters on sloped fields.

Findings

Reduced harvesting loss due to improved attitude control.

Validated system with quantitative RMSE assessment.

Potential for enhanced mechanization of cabbage harvesting.

Abstract

Korean cabbage harvesting lacks mechanization and depends on human power; thus, conducting research on Korean cabbage harvesters is of immense importance. Although these harvesters have been developed in various forms, they have not yet attained commercialization. Most Korean cabbage fields have slopes; thus there are several challenges, that can prevent accurate harvesting. Therefore, to address these challenges at the site, we adopt two cylinders in this study, develop a mechanism that enables attitude control of the cutting device, not driving platform body, to cope with slopes. By maintaining the level, angle, height of cutting, we can reduce loss and improve harvest performance. It is difficult to find examples where these mechanisms have been applied. For basic research, sensor fusion has been carried out based on the Kalman filter, which is commonly utilized for attitude control. The hydraulic cylinder was controlled using the data obtained for maintaining the attitude. Furthermore, field tests were conducted to validate this system, and the root mean square error (RMSE) was obtained and verified to quantitatively assess the presence or absence of attitude control. Therefore, the purpose of this study is to suggest a development direction for Korean cabbage harvesters via the proposed attitude control system.