摘要
为解决番茄枝叶修剪机械手无法准确找到番茄侧枝修剪点的问题,保证番茄枝叶修剪机械手工作效率,提出基于不同边缘类型的番茄侧枝特征点识别方法。在粒子群算法优化的神经网络(PSO-BP)的基础上设计“眼在手上”视觉伺服控制系统。通过对番茄植株横纵边缘分割,分别进行横向边缘和纵向边缘的提取,用阈值分割除去番茄叶片的短边缘,并记录其交点横纵坐标,限制交点分别在横向边缘的上边缘和下边缘,得到对偶的番茄侧枝点。试验结果表明,所设计的视觉伺服系统能成功的识别番茄侧枝点,仿真试验测试得到图像特征的实际值和期望值误差在3~5个像素之间,五自由度的机械手能在4 s内移动到期望位置,为农业修剪枝叶机器人进一步研究提供参考。
In order to solve the problem that the tomato branch and leaf pruning manipulator could not accurately find the pruning points of the tomato branch and leaf pruning manipulator,and to ensure the efficiency of the tomato branch and leaf pruning manipulator,a tomato branch feature point recognition method based on different edge types was proposed.Based on the neural network optimized by the particle swarm optimization algorithm(PSO-BP),in this paper,an“eye on hand”visual servo control system was designed.By dividing the horizontal and vertical edges of tomato plants,the horizontal and vertical edges were extracted,and the short edges of tomato leaves were removed by threshold segmentation.The horizontal and vertical coordinates of the intersection points were recorded.The intersection points were restricted to the upper edge and lower edge of the lateral edges to obtain the dual branch points of the tomato.The test results showed that the designed visual servo system could successfully identify the tomato side branch points.The simulation test showed that the error between the actual value and the expected value of the image feature was between 3-5 pixels,and the five-degree-of-freedom manipulator moved within 4 seconds,which provides a reference for further research on agricultural pruning robots.
作者
梁喜凤
花瑞
杨铭涛
Liang Xifeng;Hua Rui;Yang Mingtao(College of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou,310018,China)
出处
《中国农机化学报》
北大核心
2022年第7期8-13,F0002,共7页
Journal of Chinese Agricultural Mechanization
基金
国家自然科学基金资助项目(51505454、31971796)
浙江省重点研发计划/重大科技专项重点农业项目(2015C02003)。
关键词
枝叶修剪
视觉伺服
神经网络
图像处理
branch and leaf pruning
visual serving
neural network
image processing
