本文關(guān)鍵詞：蘋果采摘機(jī)器人末端執(zhí)行器無(wú)損主動(dòng)抓取技術(shù)研究　出處：《江蘇大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 蘋果采摘機(jī)器人 末端執(zhí)行器 穩(wěn)定抓取 柔順控制

【摘要】：在果蔬生產(chǎn)過(guò)程中,采摘環(huán)節(jié)是最耗時(shí)和耗力的環(huán)節(jié),人工采摘的成本約占整個(gè)生產(chǎn)成本的50%~70%。開(kāi)展采摘機(jī)器人研究,不僅有利于解決人口老齡化和社會(huì)城鎮(zhèn)化導(dǎo)致的勞動(dòng)力日益短缺問(wèn)題,還能促進(jìn)我國(guó)農(nóng)業(yè)科技進(jìn)步,加速實(shí)現(xiàn)農(nóng)業(yè)現(xiàn)代化。由于果蔬組織柔軟、易損傷且生長(zhǎng)程度不一,相互差異較大,導(dǎo)致采摘的損傷率較高。因此開(kāi)展末端執(zhí)行器抓取規(guī)劃和控制策略的研究對(duì)實(shí)現(xiàn)采摘機(jī)器人的無(wú)損采摘具有重要意義,本文從采摘機(jī)器人末端執(zhí)行器穩(wěn)定抓取規(guī)劃以及抓取力主動(dòng)柔順控制兩個(gè)角度出發(fā)對(duì)采摘機(jī)器人無(wú)損抓取技術(shù)進(jìn)行研究,主要研究?jī)?nèi)容如下:(1)基于蘋果的形態(tài)結(jié)構(gòu)特性和力學(xué)特性,設(shè)計(jì)了末端執(zhí)行器,確定了果梗切割方式。為提高末端執(zhí)行器環(huán)境感知能力,設(shè)計(jì)了包括力傳感器、碰撞傳感器和視覺(jué)傳感器在內(nèi)的末端執(zhí)行器傳感器系統(tǒng),并建立了末端執(zhí)行器的數(shù)學(xué)模型。(2)以力封閉作為理論基礎(chǔ),分析了兩指穩(wěn)定抓取條件,制定了兩指穩(wěn)定抓取策略。同時(shí)根據(jù)三指實(shí)物模型,建立三指抓取數(shù)學(xué)優(yōu)化模型,通過(guò)神經(jīng)網(wǎng)絡(luò)對(duì)優(yōu)化模型進(jìn)行擬合分析,得到抓取位置與抓取性能之間的關(guān)系。(3)根據(jù)蘋果采摘機(jī)器人末端執(zhí)行器對(duì)抓取力的要求,設(shè)計(jì)了改進(jìn)阻抗控制器。通過(guò)對(duì)阻抗控制的穩(wěn)定性分析得知力誤差與環(huán)境剛度和環(huán)境位置密切相關(guān),為了實(shí)現(xiàn)對(duì)參考力的快速跟蹤,在力控制器中,加入了遞推最小二乘法(RLS)實(shí)現(xiàn)環(huán)境剛度參數(shù)的在線辨識(shí),根據(jù)辨識(shí)得到剛度參數(shù),調(diào)整位置輸入信號(hào),減小穩(wěn)態(tài)力誤差。根據(jù)遺忘因子在RLS算法中的作用,對(duì)RLS算法進(jìn)行了修正,提出了一種基于誤差變遺忘因子的RLS算法,克服了環(huán)境參數(shù)未知對(duì)阻抗控制的影響。在Matlab中對(duì)所提出的控制算法進(jìn)行驗(yàn)證,仿真結(jié)果表明了所設(shè)計(jì)的阻抗控制器具有良好的性能。(4)分別利用改進(jìn)的阻抗控制算法和普通阻抗控制算法控制末端執(zhí)行器進(jìn)行蘋果抓取試驗(yàn)。試驗(yàn)結(jié)果表明,相對(duì)于普通阻抗控制,改進(jìn)的阻抗力控制在抓取過(guò)程中能夠快速跟蹤給定力,提高抓取的穩(wěn)定性,減少抓取損傷,能夠?qū)崿F(xiàn)主動(dòng)柔順抓取,更加符合采摘機(jī)器人抓取的應(yīng)用要求。
[Abstract]:In the process of fruit and vegetable production, picking is the most time-consuming and labor-consuming link, the cost of manual picking accounts for about 50% of the total production cost. It can not only solve the problem of labor shortage caused by aging population and urbanization, but also promote the progress of agricultural science and technology, accelerate the realization of agricultural modernization, because of the soft organization of fruits and vegetables. It is easy to damage and grow with different degrees, which leads to high damage rate of picking. Therefore, it is very important to carry out the research on the planning and control strategy of end effector grab in order to realize the non-destructive picking of picking robot. In this paper, the acquisition technology of the harvesting robot is studied from two aspects: the stable grab planning of the end actuator and the active flexibility control of the grab force. The main research contents are as follows: (1) based on the morphological and mechanical characteristics of apple, the end effector is designed, and the cutting mode of fruit-stem is determined. The end actuator sensor system including force sensor, collision sensor and vision sensor is designed, and the mathematical model of end actuator is established. The condition of two-finger stable grab is analyzed and the strategy of two-finger stable grab is worked out. At the same time, according to the three-finger physical model, the mathematical optimization model of three-finger grab is established, and the optimization model is fitted and analyzed by neural network. The relationship between the position of grab and the performance of grab is obtained.) according to the requirements of the end actuators of the apple picking robot for grasping force. Through the stability analysis of impedance control, it is found that the force error is closely related to the environment stiffness and the environment position. In order to realize the fast tracking of the reference force, the force controller is used in the force controller. Recursive least square method (RLSs) is added to realize the on-line identification of environmental stiffness parameters, according to which the stiffness parameters are obtained and the position input signals are adjusted. According to the function of forgetting factor in RLS algorithm, the RLS algorithm is modified, and a RLS algorithm based on error variable forgetting factor is proposed. It overcomes the influence of unknown environmental parameters on impedance control and verifies the proposed control algorithm in Matlab. The simulation results show that the designed impedance controller has good performance. The improved impedance control algorithm and the common impedance control algorithm are used to control the end actuator for the apple grab test. The experimental results show that. Compared with the ordinary impedance control, the improved impedance force control can quickly track the fixed force, improve the stability of the grab, reduce the grab damage, and realize the active compliant grasp. More in line with the picking robot grab application requirements.
【學(xué)位授予單位】：江蘇大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP242

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