茄果类蔬菜种苗高效嫁接机器人研制
Agricultural Engineering Technology(2020)
Abstract
嫁接是一种绿色、环保、可持续的解决土传病害的方法,但是目前嫁接作业主要依靠人工进行,存在生产率低、作业质量不稳定、劳动强度大等问题.为提高嫁接作业生产率,降低作业劳动强度,二十多年来,很多国家相继开发自动嫁接技术,但现有嫁接机作业效率和人工比没有显著优势.该文旨在开发一款茄果类高速嫁接机.为提高嫁接作业生产率,该文采取如下措施:去冠幅砧木整盘自动上苗;同步多株嫁接;捡拾机械手将砧木取出、拉大间距后移至转运杯中进行多株同步嫁接作业;负压吸附上接穗苗.该嫁接机设计为双人上接穗苗作业模式,通过控制程序调整也可实施单人作业模式.对该茄果类高速嫁接机样机进行上苗试验及整机性能试验,试验结果表明,双人作业模式生产率可达2250株/h,单人作业模式生产率可达1542株/h,明显高于现有嫁接机,与人工嫁接作业生产率相比具有较大优势.目前,该嫁接机的作业能力超过了单人上苗的速度,但仍低于双人上苗速度,因此,对于双人上苗最大速度,通过对该嫁接机进行结构、作业方式的优化,嫁接机的生产率仍有提高空间.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2011
被引用19 | 浏览
2012
被引用11 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper