Authors

Abstract

Kiwifruit picking robots can replace manual labor for mechanized kiwifruit harvesting. However, existing picking robots encounter issues such as low separation efficiency of fruit stalks, poor stability of fruit gripping, and inaccurate identification when picking kiwifruit clusters. In response, a multi-fruit picking end-effector was designed to pick clusters of kiwifruit efficiently based on their distribution characteristics. The gripping range of the gripping device was determined based on the parameters of the spatial distribution of the fruit clusters. A multi-fruit gripping mechanics model was constructed, and the gripping force was analyzed to ensure efficient and stable fruit picking. Critical parameters of the fruit stalk separation device were determined through kinematic trajectory analysis to improve the separation efficiency of fruit stalks. Additionally, a dual-sensor fusion recognition method was proposed to identify fruit cluster locations accurately. The results of the picking experiment demonstrate that the end-effector can pick fruits in an average time of 8.28 s per cluster, with a net fruit-picking rate of 87.5% and a fruit damage rate of 7.5%. The end-effector shows a positive picking effect on kiwifruit fruits distributed in clusters. This study can serve as a reference for the development of kiwifruit-picking robots.

Abstract in Chinese

猕猴桃采摘机器人可替代人工劳作实现猕猴桃机械化收获。但现有采摘机器人采摘成簇分布猕猴桃时，末端执行器存在果梗分离效率低、果实夹持稳定性差、果实识别准确度低等问题。对此，本文根据猕猴桃果实的分布特征，设计了一种多果夹持切割联动式采摘末端执行器，以期实现成簇果实的快速采摘作业。根据果实簇空间分布参数确定夹持装置夹持范围，构建多果稳定夹持力学模型并对夹持力进行分析，基于运动学轨迹分析确定果梗剪切装置关键参数。在此基础上，提出了一种双传感器融合识别方法以实现果实簇位置的准确判别。采摘试验结果表明该末端执行器采摘每簇果实平均时间为8.28s，果实净采摘率为87.5%，果实损伤率为7.5%，对簇生分布的猕猴桃果实有良好采摘效果。该研究可为猕猴桃采摘机器人研制提供参考。