梨
果园
机器人
运动学
计算机科学
计算机视觉
模拟退火
模拟
人工智能
实时计算
工程类
算法
物理
经典力学
万维网
园艺
生物
作者
Hewen Zhang,Xiaoguang Li,Ling Wang,Dian Liu,Shubo Wang
出处
期刊:Agronomy
[MDPI AG]
日期:2023-12-28
卷期号:14 (1): 80-80
标识
DOI:10.3390/agronomy14010080
摘要
In order to meet the needs of intensive mechanized picking in trellised pear orchards, this paper designed a pick-place integrated end-picker based on the analysis of agronomic characteristics of trellised pear gardens and fruit. In order to realize the accurate positioning of pears in picking, based on the kinematic analysis of robot arms and the construction of a private dataset, the YOLOv5s object detection algorithm was used in conjunction with a depth camera to achieve fruit positioning. The hand–eye system calibration was carried out. Aiming at solving the problems of redundancy, inefficiency, and uneven distribution of task volume in the conventional multiple robot arms algorithm, a simulated annealing algorithm was introduced to optimize the picking sequence, and a task allocation method was proposed. On the basis of studying several key parameters affecting the performance of the algorithm, the picking efficiency was greatly optimized. And the effectiveness of the proposed multi-robot collaborative picking method in a trellised pear orchard environment was demonstrated through experiments and simulation verification. The experiments showed that the picking efficiency of the integrated end-picker was increased by about 30%, and the success rate was significantly higher than that of the flexible grippers. The results of this study can be utilized to advance robotic pear-picking research and development.
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