摘要
针对采摘机器人果实识别速率较低导致采摘效率较低的问题,对数据挖掘技术在采摘机器人中图像采集过程的应用进行了分析。采摘机器人主要组成包括图像采集模块、运动控制模块、气压驱动模块、电源模块、微处理器模块和无线网传输模块。为了提升图像数据的处理速度,采用MR模型和决策树中的ID_(3)算法对图像数据进行处理,并构建决策树模型,对图像数据进行数据挖掘处理。为了验证该采摘机器人的性能,对其进行数据挖掘算法调试试验和采摘机器人性能试验,结果表明:该图像处理算法速度显著提升,采摘机器人性能稳定,采摘效果好。
Aiming at the problem of low fruit recognition rate,and then lead to low picking efficiency of picking robot,the application of data mining technology to image acquisition process of picking robot was analysed and studied.The picking robot was constituted of map acquisition module,motion control module,pneumatic drive module,power module,microprocessor module and wireless network transmission module.To improve the process speed of image data,the image data was processed by MR and the ID_(3) algorithm in the decision tree.And the decision tree was built for image data to be processed by data mining technology.To verify the performance of the picking robot,the data mining algorithm adapted test and picking robot performance test were carried out.The test results show that the speed of the data process algorithm is improved significantly.The performance of the picking robot is stable and the picking effect is well.
作者
白俊
Bai Jun(Beijing Jingbei Vocational and Technical College,Beijing 101400,China)
出处
《农机化研究》
北大核心
2022年第7期192-195,共4页
Journal of Agricultural Mechanization Research
基金
国家自然科学基金项目(60973011)。