本文關(guān)鍵詞： 位姿測量 傾角傳感器 參數(shù)標(biāo)定 組合測量 單目視覺　出處：《天津大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：空間物體的位姿是反映物體的重要參數(shù),隨著空間物體位姿測量需求的不斷提升,空間物體的位姿測量越來越受到人們的重視,廣泛應(yīng)用在工業(yè)、軍事、大型裝備制造、航空航天等領(lǐng)域,傳統(tǒng)的空間物體相對位姿測量方法從原理上可以概括為四大類:基于激光跟蹤測量系統(tǒng)的位姿測量方法、基于慣性導(dǎo)航系統(tǒng)的位姿測量方法、基于機(jī)械定位約束的位姿測量方法和基于計(jì)算機(jī)視覺系統(tǒng)的視覺位姿測量方法。本文針對視覺相對位姿測量中存在的問題,研究了一種視覺與傾角傳感器組合的相對位姿測量方法,通過在相機(jī)和被測物上各放置一個(gè)傾角傳感器,利用固定傾角傳感器所提供的角度信息提供額外的約束來求解Pn P(Perspective-n-Point)問題,文章介紹了組合相對位姿測量方法的原理及其結(jié)構(gòu)參數(shù)標(biāo)定,為了提高算法的精度和抗噪能力,在求得線性解的基礎(chǔ)上進(jìn)一步進(jìn)行非線性優(yōu)化,仿真實(shí)驗(yàn)驗(yàn)證了該方法的正確性,并與現(xiàn)存的Pn P問題求解方法比較,表明本課題研究的Pn P問題求解方法具有較高精度并且對噪聲干擾具有較高的穩(wěn)定性,最后,實(shí)驗(yàn)結(jié)果表明本文研究的方法對空間15個(gè)特征點(diǎn)在x方向和y方向的平均反投影誤差均小于為0.2 pixel,能夠滿足空間物體位姿測量精度需求。本文主要的研究工作和創(chuàng)新點(diǎn)如下:1、廣泛查閱國內(nèi)外相關(guān)研究文獻(xiàn)資料,分析位姿測量研究的意義和國內(nèi)外研究現(xiàn)狀,闡述本課題的研究價(jià)值和意義。2、針對傳統(tǒng)視覺位姿測量求解過程中存在的問題,研究了視覺與傾角傳感器組合相對位姿測量方法,利用視覺和傾角傳感器的測量信息求解Pn P問題,詳細(xì)推導(dǎo)了組合位姿測量原理,設(shè)計(jì)組合位姿測量算法,為了提高算法的求解精度和抗噪能力,在求得線性解的基礎(chǔ)上進(jìn)一步進(jìn)行非線性優(yōu)化,提高求解精度,并進(jìn)行仿真實(shí)驗(yàn),驗(yàn)證組合測量原理的正確性。3、歸納總結(jié)了組合位姿測量圖像傳感器標(biāo)定的基本理論和方法,根據(jù)相機(jī)成像模型,推導(dǎo)相機(jī)內(nèi)外參數(shù)標(biāo)定原理,完成了相應(yīng)算法的編寫與仿真分析。4、根據(jù)視覺與傾角傳感器組合位姿測量原理,研究了組合位姿測量系統(tǒng)結(jié)構(gòu)參數(shù)標(biāo)定方法,推導(dǎo)組合位姿測量系統(tǒng)結(jié)構(gòu)參數(shù)標(biāo)定原理,并利用仿真實(shí)驗(yàn)驗(yàn)證組合位姿測量系統(tǒng)結(jié)構(gòu)參數(shù)標(biāo)定原理的正確性。5、設(shè)計(jì)編寫視覺與傾角傳感器組合位姿測量系統(tǒng)相關(guān)算法,并進(jìn)行實(shí)驗(yàn)分析各測量因素對組合位姿測量精度的影響。
[Abstract]:The pose of space object is an important parameter to reflect the object. With the increasing demand of position and attitude measurement of space object, more and more attention has been paid to the pose measurement of space object, which has been widely used in industry and military. In the field of large-scale equipment manufacturing, aerospace and other fields, the traditional relative position and attitude measurement methods of space objects can be summarized into four categories in principle: the position and attitude measurement method based on laser tracking measurement system. The position and pose measurement method based on inertial navigation system, the position and pose measurement method based on mechanical positioning constraint and the vision position and attitude measurement method based on computer vision system. In this paper, a method of measuring the relative position and attitude of the combination of vision and inclination sensor is studied. One inclination sensor is placed on the camera and the object being tested. The angle information provided by the fixed inclination sensor is used to provide additional constraints to solve the problem of PN Perspective-n-Point. This paper introduces the principle of combined relative pose measurement method and its structural parameter calibration. In order to improve the accuracy and anti-noise ability of the algorithm, the nonlinear optimization is carried out on the basis of finding the linear solution. The simulation results show that the method is correct and compared with the existing PN P problem solving method. It shows that the solution method of PN P problem studied in this paper has high accuracy and high stability to noise interference. Finally. The experimental results show that the average backprojection error of the method is less than 0. 2 pixel in x direction and y direction for 15 feature points in space. The main research work and innovation of this paper are as follows: 1. This paper analyzes the significance of the position and pose measurement research and the current research situation at home and abroad, expounds the research value and significance of this topic, aiming at the problems existing in the traditional vision pose measurement process. The relative pose measurement method of the combination of vision and inclination sensor is studied. The measurement information of vision and inclination sensor is used to solve the PN P problem, and the principle of combined position and attitude measurement is deduced in detail. In order to improve the accuracy and anti-noise ability of the combined pose measurement algorithm, the nonlinear optimization is carried out on the basis of the linear solution, and the accuracy of the solution is improved, and the simulation experiment is carried out. Verify the correctness of the combined measurement principle. 3. Summarize the basic theory and method of the combined position and attitude measurement image sensor calibration. According to the camera imaging model, the principle of camera internal and external parameters calibration is deduced. The corresponding algorithm is compiled and simulated. 4. According to the principle of combined position and attitude measurement of vision and inclination sensor, the calibration method of structural parameters of combined position and attitude measurement system is studied. The principle of structure parameter calibration of combined position and attitude measurement system is deduced, and the correctness of structure parameter calibration principle of combined position and attitude measurement system is verified by simulation experiment. The related algorithms of the combined position and pose measurement system of the vision and inclination sensor are designed and the influence of various measurement factors on the combined position and pose measurement accuracy is analyzed experimentally.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TP391.41;TP212

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