火龙果采摘机械手控制系统设计与试验文献综述

 2022-01-09 21:19:22

全文总字数:8845字

摘要

火龙果有“果中之王”的赞誉,其营养价值丰富,口感香甜,深受中国大众的喜爱。2019年,中国鲜火龙果进口量和进口额分别为43.57万吨和36213.95万美元,出口量和出口额分别为0.51万吨和903.72万美元,全年火龙果进出口表现为巨大的贸易逆差,表明我国对火龙果的需求大,火龙果市场日益火爆,因此在我国的种植规模也越来越大。然而,目前火龙果的收获方式仍是人工采摘为主,效率低,成本高,其智能化采摘的需求日益迫切,适用于大棚种植的火龙果自动采摘机械仍处于研发阶段,其中控制系统尤为关键。本文以机器视觉为手段,结合数字图像处理,微电子技术,传感器技术,人工势场方法,计算机软硬件技术等知识,基于MCS–51系列单片机的火龙果采摘机械手控制系统的设计与试验。测试结果显示:所设计的采摘机械手具有一定的避障能力,有较高的识别精度和较快的识别速度,能满足农户火龙果采摘的需求。

关键词:机器视觉;控制系统;传感器;人工势场;单片机

Design and test of control system of pitaya picking manipulator

Abstract

Pitaya is praised as 'the king of fruits', with its rich nutritional value and sweet taste, which is deeply loved by the Chinese public.Fresh pitaya in 2019, China#39;s imports and imports of 435700 m and $362.1395 million respectively, exports and export share of 05100 m and $9.0372 million respectively, pitaya import and export for the whole year show the large trade deficit with China, suggests that China#39;s demand for pitaya, dragon fruit market is increasingly hot, so the scale of planting in our country is becoming more and more big.However, at present, the harvest method of pitaya is still mainly manual picking, which is low in efficiency and high in cost. The demand for intelligent picking is increasingly urgent. The automatic picking machine suitable for greenhouse planting is still in the research and development stage, and the control system is particularly critical.In this paper, machine vision as a means, combined with digital image processing, microelectronics technology, sensor technology, artificial potential field method, computer hardware and software technology and other knowledge, based on MCS-51 series of single-chip microcomputer pitaya picking manipulator control system design and test.The test results show that the designed picking manipulator has a certain ability to avoid obstacles, higher identification accuracy and faster identification speed, which can meet the needs of farmers#39; pitaya picking.

Key words: machine vision;Control system;The sensor;Artificial potential field;Single chip microcomputer

目录

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