發(fā)布時間：2018-03-10 13:38

  本文選題：移動機(jī)器人定位　切入點(diǎn)：慣性導(dǎo)航　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：移動機(jī)器人的定位是自主導(dǎo)航研究的基礎(chǔ),也是移動機(jī)器人領(lǐng)域的重要研究課題。本論文的主要研究內(nèi)容是基于ROS操作系統(tǒng),將慣性導(dǎo)航和視覺傳感器信息融合,解決移動機(jī)器人自主定位的問題。目前,單目SLAM存在初始化的尺度問題和追蹤的尺度漂移問題;慣性導(dǎo)航數(shù)據(jù)穩(wěn)定,但積累誤差更為嚴(yán)重。這兩種技術(shù)的融合可以將單目視覺SLAM的高精度與慣性導(dǎo)航數(shù)據(jù)的穩(wěn)定性結(jié)合起來,取長補(bǔ)短,達(dá)到滿足定位精度的目的。具體研究內(nèi)容如下:第一,研究了捷聯(lián)慣性導(dǎo)航系統(tǒng)的基本定位理論,包括慣性導(dǎo)航坐標(biāo)系,基本旋轉(zhuǎn)理論和基于四元數(shù)算法的姿態(tài)解算的知識以及航位推算的理論。為進(jìn)一步研究和應(yīng)用奠定了基礎(chǔ)。并進(jìn)行實(shí)驗(yàn)測試了慣性導(dǎo)航的定位精度;第二,研究了移動機(jī)器人視覺定位的理論依據(jù)。首先介紹了攝像機(jī)成像與四種坐標(biāo)系之間的關(guān)系。建立了相機(jī)成像模型,標(biāo)定相機(jī)內(nèi)參數(shù)。在此基礎(chǔ)上,推導(dǎo)了移動機(jī)器人視覺定位技術(shù)相關(guān)的POSIT算法;第三,由于慣導(dǎo)和單目SLAM屬于局部定位方法,缺少全局信息從而累積誤差無法修正。本文研究融合慣導(dǎo)的視覺同時定位與地圖構(gòu)建方法,提出基于ORB_SLAM系統(tǒng)融合IMU信息的視覺慣導(dǎo)SLAM算法(VI_SLAM),并推導(dǎo)了視覺慣導(dǎo)SLAM系統(tǒng)的初始化算法。定位實(shí)驗(yàn)部分采用控制變量法,很好地驗(yàn)證了VI_SLAM融合算法的優(yōu)越性和可靠性;第四,介紹整個平臺的硬件與軟件系統(tǒng)和實(shí)驗(yàn)部分。首先介紹了實(shí)驗(yàn)中使用的硬件和軟件平臺,并建立了雙輪差速移動機(jī)器人的運(yùn)動模型。簡述了ROS操作系統(tǒng)及其常用功能,以及導(dǎo)航與定位的基礎(chǔ)知識。實(shí)驗(yàn)的分析和設(shè)計(jì)考慮了多種不同情況的對比。提供了有效的,誤差和定位精度的分析方法。實(shí)驗(yàn)分析表明,慣性導(dǎo)航和單目SLAM方法的結(jié)合有效提高了定位精度,展示了該算法的實(shí)際應(yīng)用前景。
[Abstract]:The localization of mobile robot is the basis of autonomous navigation and an important research topic in the field of mobile robot. The main research content of this paper is based on ROS operating system, the inertial navigation and vision sensor information fusion. To solve the problem of autonomous positioning of mobile robot. At present, monocular SLAM has initialization scale problem and tracking scale drift problem, inertial navigation data is stable, But the accumulation error is more serious. The fusion of these two techniques can combine the high precision of monocular vision SLAM and the stability of inertial navigation data, learn from each other, and achieve the purpose of satisfying the positioning accuracy. The specific research contents are as follows: first, The basic positioning theory of strapdown inertial navigation system, including inertial navigation coordinate system, is studied. The basic theory of rotation, the knowledge of attitude solution based on quaternion algorithm and the theory of dead-reckoning lay the foundation for further research and application. The positioning accuracy of inertial navigation is tested experimentally. The theoretical basis of vision positioning of mobile robot is studied. Firstly, the relationship between camera imaging and four coordinate systems is introduced. The camera imaging model is established and the camera internal parameters are calibrated. The POSIT algorithm related to the vision positioning technology of mobile robot is deduced. Thirdly, because inertial navigation and monocular SLAM belong to local localization method, Because of the lack of global information, the accumulated error can not be corrected. In this paper, the visual simultaneous location and map construction method of fusion inertial navigation system are studied. A visual inertial navigation (SLAM) algorithm based on ORB_SLAM system fusion IMU information is proposed, and the initialization algorithm of visual inertial navigation (SLAM) system is derived. The control variable method is used in the positioning experiment, which verifies the superiority and reliability of VI_SLAM fusion algorithm. 4th, The hardware and software system and experiment part of the whole platform are introduced. Firstly, the hardware and software platform used in the experiment is introduced, and the motion model of the two-wheel differential mobile robot is established. The ROS operating system and its common functions are briefly described. And the basic knowledge of navigation and positioning. The analysis and design of the experiment take into account the comparison of many different situations. It provides an effective analysis method for error and positioning accuracy. The experimental analysis shows that, The combination of inertial navigation and monocular SLAM method can effectively improve the positioning accuracy and demonstrate the practical application prospect of the algorithm.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TP242
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本文編號：1593582