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Structural Parameter Optimization of a Tomato Robotic Harvesting Arm: Considering Collision-Free Operation Requirements

文献类型： 外文期刊

作者： Peng, Chuanlang 1 ; Feng, Qingchun 1 ; Guo, Zhengwei 2 ; Ma, Yuhang 2 ; Li, Yajun 2 ; Zhang, Yifan 2 ; Gao, Liangzheng 2 ;

作者机构： 1.Xinjiang Agr Univ, Coll Mech & Elect Engn, Urumqi 830052, Peoples R China

2.Beijing Acad Agr & Forestry Sci, Intelligent Equipment Res Ctr, Beijing 100097, Peoples R China

3.Beijing Key Lab Intelligent Equipment Technol Agr, Beijing 100097, Peoples R China

关键词： tomato; harvesting robot; robotic arm; structural parameter optimization; collision-free

期刊名称：PLANTS-BASEL （ 影响因子：4.1； 五年影响因子：4.5 ）

ISSN： 2223-7747

年卷期： 2024 年 13 卷 22 期

页码：

收录情况： SCI

摘要： The current harvesting arms used in harvesting robots are developed based on standard products. Due to design constraints, they are unable to effectively avoid obstacles while harvesting tomatoes in tight spaces. To enhance the robot's capability in obstacle-avoidance picking of tomato bunches with various postures, this study proposes a geometric parameter optimization method for a 7 degree of freedom (DOF) robotic arm. This method ensures that the robot can reach a predetermined workspace with a more compact arm configuration. The optimal picking posture for the end-effector is determined by analyzing the spatial distribution of tomato bunches, the main stem position, and peduncle posture, enabling a quantitative description of the obstacle-avoidance workspace. The denavit-hartenberg (D-H) model of the harvesting arm and the expected collision-free workspace are set as constraints. The compactness of the arm and the accessibility of the harvesting space serve as the optimization objectives. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective genetic algorithm is employed to optimize the arm length, and the results were validated through a virtual experiment using workspace traversal. The results indicate that the optimized structure of the tomato harvesting arm is compact, with a reachability of 92.88% in the workspace, based on the collision-free harvesting criteria. This study offers a reference for structural parameter optimization of robotic arms specialized in fruit and vegetable harvesting.

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