Deviation Tolerance Performance Evaluation and Experiment of Picking End Effector for Famous Tea

Author:

Zhu YingpengORCID,Wu Chuanyu,Tong Junhua,Chen Jianneng,He LeiyingORCID,Wang RongyangORCID,Jia JiangmingORCID

Abstract

Accurately obtaining the posture and spatial position of tea buds through machine vision and other technologies is difficult due to the small size, different shapes, and complex growth environment of tea buds. Therefore, end effectors are prone to problems, such as picking omission and picking error. This study designs a picking end effector based on negative pressure guidance for famous tea. This end effector uses negative pressure to guide tea buds in a top-down manner, thereby correcting their posture and spatial position. Therefore, the designed end effector has deviation tolerance performance that can improve the picking success rate. The pre-experiment is designed, the tip of apical bud is referred to as the descent position, and the negative pressure range is determined to be 0.6 to 0.9 kPa. A deviation tolerance orthogonal experiment is designed. Experimental results show that various experimental factors are ranked in terms of the significance level of the effect on the average success rate, and the significance ranking is as follows: negative pressure (P) > pipe diameter (D) > descent speed (V). An evaluation method of deviation tolerance performance is presented, and the optimal experiment factor-level combination is determined as: P = 0.9 kPa, D = 34 mm, V = 20 mm/s. Within the deviation range of a 10 mm radius, the average success rate of the negative pressure guidance of the end effector is 97.36%. The designed end effector can be applied to the intelligent picking of famous tea. This study can provide a reference for the design of similar picking end effectors for famous tea.

Funder

the Post Scientist of the Modern Agriculture Industry System (Intelligent Tea Picking) of the Ministry of Agriculture and Rural Affairs of the People’s Republic of China

Publisher

MDPI AG

Subject

Plant Science,Agronomy and Crop Science,Food Science

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