【摘要】：隨著生產(chǎn)力水平的不斷進(jìn)步和科學(xué)技術(shù)的飛速發(fā)展,工業(yè)機(jī)器人作為先進(jìn)、智能的工業(yè)化設(shè)備的代表,在社會生活的很多方面應(yīng)用廣泛,尤其在汽車產(chǎn)業(yè)領(lǐng)域得到了相當(dāng)成熟和廣泛的應(yīng)用。車身的尺寸偏差是影響車身質(zhì)量最重要的因素,以工業(yè)機(jī)器人車身激光檢測系統(tǒng)為代表的車身尺寸檢測技術(shù)已成為當(dāng)前全球車企降低車身尺寸偏差,提升車身制造精度最為有效的手段之一,對于工業(yè)機(jī)器人定位精度的研究具有非常重要的工程意義和經(jīng)濟(jì)意義。首先,本論文以工業(yè)機(jī)器人車身激光檢測系統(tǒng)中最常用的KUKA工業(yè)機(jī)器人為例,對其運(yùn)動學(xué)問題進(jìn)行了理論剖析,闡述了建立正向運(yùn)動學(xué)模型和求解運(yùn)動學(xué)逆解的方法,使用MATLAB Robotics Toolbox進(jìn)行了運(yùn)動學(xué)模型的仿真驗證。其次,在運(yùn)動學(xué)模型的基礎(chǔ)上,考慮影響工業(yè)機(jī)器人定位精度最大的幾何誤差因素,采用微分的方法建立了幾何偏差模型;在考慮車身激光檢測工程應(yīng)用的基礎(chǔ)上,分析了車身定位坐標(biāo)系與機(jī)器人激光測量坐標(biāo)系不重合對工業(yè)機(jī)器人定位精度造成的耦合影響,并依此在幾何偏差模型的基礎(chǔ)上建立了基于車身激光檢測系統(tǒng)的KUKA工業(yè)機(jī)器人車身定位誤差模型,并對該模型進(jìn)行了仿真驗證,確定了其有效性和準(zhǔn)確性。再次,在進(jìn)行工業(yè)機(jī)器人定位誤差補(bǔ)償方法的研究時,首先基于所建立的工業(yè)機(jī)器人車身定位誤差模型,使用牛頓-拉夫遜迭代算法進(jìn)行了仿真驗證。考慮到基于誤差模型進(jìn)行定位誤差補(bǔ)償?shù)木窒扌?設(shè)計了合適的BP神經(jīng)網(wǎng)絡(luò)對KUKA機(jī)器人的誤差模型進(jìn)行網(wǎng)絡(luò)逼近并進(jìn)行了誤差補(bǔ)償,并且完成了對比仿真實(shí)驗。結(jié)果表明,采用BP神經(jīng)網(wǎng)絡(luò)進(jìn)行定位誤差補(bǔ)償比基于誤差模型進(jìn)行定位誤差補(bǔ)償?shù)难a(bǔ)償精度更高。最后,考慮到傳統(tǒng)BP神經(jīng)網(wǎng)絡(luò)收斂速率慢等問題,提出采用PSO算法與BP神經(jīng)網(wǎng)絡(luò)相結(jié)合的算法,對BP神經(jīng)網(wǎng)絡(luò)進(jìn)行優(yōu)化,使KUKA機(jī)器人定位誤差補(bǔ)償?shù)男Ч选?br/>[Abstract]:With the continuous progress of productivity and the rapid development of science and technology, industrial robots, as the representatives of advanced and intelligent industrial equipment, are widely used in many aspects of social life. Especially in the field of automobile industry has been quite mature and widely used. The dimension deviation of the body is the most important factor that affects the quality of the body. The measurement technology of the car body size, which is represented by the laser inspection system of the industrial robot body, has become the current global automobile enterprises to reduce the body size deviation. One of the most effective means to improve the precision of body manufacturing is of great engineering and economic significance for the research of positioning accuracy of industrial robots. Firstly, taking the KUKA industrial robot, which is the most commonly used industrial robot in the body laser detection system of industrial robot, as an example, the kinematics problem is analyzed theoretically, and the method of establishing forward kinematics model and solving the inverse kinematics solution is expounded. The kinematics model is simulated with MATLAB Robotics Toolbox. Secondly, on the basis of kinematics model, considering the geometric error factors that affect the positioning accuracy of industrial robot, the differential method is used to establish the geometric deviation model. The coupling effect on the positioning accuracy of industrial robots caused by the non-coincidence of body positioning coordinate system and robot laser measuring coordinate system is analyzed. Based on the geometric deviation model, the body positioning error model of KUKA industrial robot based on body laser detection system is established. The simulation results show that the model is effective and accurate. Thirdly, in the research of the positioning error compensation method of industrial robot, the Newton-Raphson iterative algorithm is used to verify the error model of industrial robot body positioning. Considering the limitation of positioning error compensation based on error model, a suitable BP neural network is designed to approximate and compensate the error model of KUKA robot, and a comparative simulation experiment is completed. The results show that the compensation accuracy of positioning error based on BP neural network is higher than that based on error model. Finally, considering the slow convergence rate of traditional BP neural network, an algorithm combining PSO algorithm with BP neural network is proposed to optimize the BP neural network, so that the positioning error compensation of KUKA robot is better.
【學(xué)位授予單位】：長春工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP242

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