首页|基于形态学的采摘系统视觉控制研究

基于形态学的采摘系统视觉控制研究

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以进一步提升采摘机器人系统的作业效率为目标,选取形态学算法作为支撑机理与参考基点,针对采摘系统的视觉控制展开设计.考虑采摘系统的模块分工与功能组成,搭建形态学图像检测与处理模型,并进行系统的整体布局与软硬件模块匹配,形成以形态学运算处理规则为主的采摘机器人控制系统.采摘作业控制试验结果表明:基于形态学的采摘系统视觉控制设计方案正确可行,在形态学运算程序的精准执行下,图像特征区别效率与目标识别准确率均得到明显改善,视觉定位时间误差相对降低了 3.19%,整体系统的综合效率可达 92.30%,满足智能采摘的设计要求.系统各组件运行平稳,采摘回放动作柔性可靠,可为类似智能收获装置创新优化提供一定的参考.
Visual Control of the Picking System Based on Morphology
With the goal of further improving the operational efficiency of the picking robot system,morphological algo-rithms were selected as the supporting mechanism and reference point to design and study the visual control of the picking system.Considering the module division and functional composition of the picking system,a morphological image detec-tion and processing model was established.The overall layout of the system was conducted and the software and hardware modules were matched to form a picking robot control system based on morphological operation processing rules.Conduc-ting the picking operation control experiments,and the results showed that the visual control design scheme of the picking system based on morphology was correct and feasible.With the precise execution of the morphological operation program,the efficiency of image feature differentiation and the accuracy of target recognition had been significantly improved,the visual positioning time error had been relatively reduced by 3.19%,and the overall system efficiency could reach 92.30%,which could meet the design requirements of intelligent picking.The system components run smoothly,and the picking and playback actions were flexible and reliable.This design concept had good inspiration and promotion,and would provide certain reference value for researchers to innovate and optimize similar intelligent picking devices.

picking robotmorphological algorithmsvisual controlefficiency of image feature differentiationintelli-gent picking

刘悦

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国家农产品现代物流工程技术研究中心,济南 250103

山东省农产品贮运保鲜技术重点实验室,济南 250103

采摘机器人 形态学算法 视觉控制 图像特征区别效率 智能采摘

2025

农机化研究
黑龙江省农业机械工程科学研究院 黑龙江省农业机械学会

农机化研究

北大核心
影响因子:0.668
ISSN:1003-188X
年,卷(期):2025.47(3)