發(fā)布時(shí)間：2018-05-27 23:29

  本文選題：車載激光測(cè)量系統(tǒng) + 點(diǎn)云�。� 參考：《首都師范大學(xué)》2013年碩士論文

【摘要】：隨著公路交通行業(yè)的快速發(fā)展,新增路網(wǎng)大量需求,又由于早期建成的公路設(shè)計(jì)標(biāo)準(zhǔn)較低和超大服役等因素,使得道路新建、改建、擴(kuò)建、維護(hù)等工程對(duì)專業(yè)測(cè)量的高效、精確、快速、安全等需求日益迫切,車載LiDAR (Light Detection And Ranging)技術(shù)應(yīng)運(yùn)而生。車載激光測(cè)量系統(tǒng)可以快速采集公路三維信息,包含點(diǎn)云坐標(biāo)、屬性信息、影像數(shù)據(jù)等,點(diǎn)云具有精度高、信息豐富等特性。車載LiDAR技術(shù)應(yīng)用于公路測(cè)量相關(guān)任務(wù),對(duì)提高效率和節(jié)約成本具有重大意義。 本文簡(jiǎn)要介紹了利用車載激光測(cè)量系統(tǒng)進(jìn)行公路數(shù)據(jù)采集的工作方法以及技術(shù)要點(diǎn),然后詳細(xì)闡述了基于車載點(diǎn)云的公路三維建模方法,并對(duì)關(guān)鍵算法進(jìn)行了設(shè)計(jì)與實(shí)現(xiàn),主要包括地面點(diǎn)濾波、數(shù)據(jù)修補(bǔ)與抽稀、點(diǎn)云構(gòu)網(wǎng)以及特征地物分類提取等內(nèi)容。原始數(shù)據(jù)包含路面、護(hù)欄、車輛、附屬設(shè)施、樹木和草叢等信息,首先采用基于掃描線的濾波方法將地面點(diǎn)與非地面點(diǎn)分離,接著對(duì)因遮擋造成的路面數(shù)據(jù)損失進(jìn)行修補(bǔ),并可以有選擇性地進(jìn)行數(shù)據(jù)抽稀,然后基于掃描線間三角剖分的方法構(gòu)建三角網(wǎng)；另外,本文特征地物分類提取的研究對(duì)象是樹和路燈,主要根據(jù)其各自空間形態(tài)特點(diǎn)進(jìn)行。 目前,車載激光測(cè)量系統(tǒng)的應(yīng)用日漸增多,車載點(diǎn)云處理技術(shù)也亟待完善,針對(duì)不同專業(yè)應(yīng)用領(lǐng)域需要有相應(yīng)的處理技術(shù)和方法。本研究即對(duì)車載LiDAR技術(shù)應(yīng)用于公路三維信息獲取與建模提出了解決方案和關(guān)鍵技術(shù)方法,并選取了一段具有代表性的公路點(diǎn)云數(shù)據(jù),對(duì)提出的方法進(jìn)行了驗(yàn)證分析,得到了較理想的結(jié)果。結(jié)果證明,車載點(diǎn)云的精度滿足公路測(cè)量精度需求,基于車載點(diǎn)云生成的公路三維模型可以實(shí)現(xiàn)公路勘測(cè)相關(guān)應(yīng)用,如生成縱、橫切面剖面圖,計(jì)算面積和土方量,查詢?nèi)我恻c(diǎn)位信息,動(dòng)畫展示和水淹沒分析等,該技術(shù)可應(yīng)用于公路勘測(cè)設(shè)計(jì)和改擴(kuò)建、公路基礎(chǔ)設(shè)施普查、公路景觀可視化等工程。
[Abstract]:With the rapid development of highway traffic industry, a large number of new road network demand, and due to the early built highway design standards and oversized service and other factors, such as road construction, reconstruction, expansion, maintenance and other projects to professional survey efficiency. The demand of precision, speed and security is more and more urgent. The LiDAR Light Detection And Ranging) technology emerges as the times require. The vehicle laser measurement system can quickly collect 3D highway information, including point cloud coordinates, attribute information, image data, etc. The point cloud has the characteristics of high accuracy and rich information. It is of great significance to improve the efficiency and save the cost by applying the LiDAR technology to highway survey related tasks. This paper briefly introduces the working method and technical points of highway data acquisition using vehicle-mounted laser measurement system, and then expounds the road 3D modeling method based on vehicle point cloud in detail, and designs and implements the key algorithm. It mainly includes ground point filtering, data repairing and thinning, point cloud structure network and feature classification and extraction. The original data includes road surface, guardrail, vehicle, ancillary facilities, trees and grass. Firstly, the ground point is separated from the non-ground point by the method of scanning line filtering, and then the road surface data loss caused by occlusion is repaired. The data can be thinned selectively, and then triangulation can be constructed based on the method of triangulation between scanning lines. In addition, tree and street lamp are the research objects of feature extraction in this paper, which are mainly based on their spatial morphological characteristics. At present, the application of vehicle laser measurement system is increasing day by day, and the point cloud processing technology of vehicle needs to be improved urgently, and the corresponding processing techniques and methods are needed for different professional application fields. In this study, we put forward the solution and key technology methods for the application of vehicle-mounted LiDAR technology in highway 3D information acquisition and modeling, and selected a representative section of road point cloud data, and analyzed the proposed method. A better result is obtained. The results show that the accuracy of vehicle point cloud can meet the needs of highway measurement accuracy, and the highway 3D model based on vehicle point cloud can be used for highway survey, such as the generation of longitudinal and cross-sectional profiles, the calculation of area and earthwork. The technology can be used in highway survey, design, reconstruction and extension, highway infrastructure survey, highway landscape visualization and so on.
【學(xué)位授予單位】：首都師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：P225.2;U412.2

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 馬利;謝孔振;白文斌;白建軍;;地面三維激光掃描技術(shù)在道路工程測(cè)繪中的應(yīng)用[J];北京測(cè)繪;2011年02期

2 李永強(qiáng);盛業(yè)華;劉會(huì)云;張卡;戴華陽;;基于車載激光掃描的公路三維信息提取[J];測(cè)繪科學(xué);2008年04期

3 黃承亮;吳侃;向娟;;三維激光掃描點(diǎn)云數(shù)據(jù)壓縮方法[J];測(cè)繪科學(xué);2009年02期

4 李卉;李德仁;黃先鋒;鐘成;;一種漸進(jìn)加密三角網(wǎng)LIDAR點(diǎn)云濾波的改進(jìn)算法[J];測(cè)繪科學(xué);2009年03期

5 楊長強(qiáng);葉澤田;盧秀山;吳俁;;車載激光點(diǎn)云數(shù)據(jù)的柵格化處理[J];測(cè)繪科學(xué);2009年05期

6 路興昌;張學(xué)霞;;基于回波強(qiáng)度和采樣點(diǎn)距離的點(diǎn)云濾波研究[J];測(cè)繪科學(xué);2009年06期

7 鄒曉亮;于英;張永生;趙桂華;;基于車載激光掃描數(shù)據(jù)的電線桿自動(dòng)識(shí)別與定位[J];測(cè)繪科學(xué);2012年02期

8 史文中,李必軍,李清泉;基于投影點(diǎn)密度的車載激光掃描距離圖像分割方法[J];測(cè)繪學(xué)報(bào);2005年02期

9 楊必勝;魏征;李清泉;毛慶洲;;面向車載激光掃描點(diǎn)云快速分類的點(diǎn)云特征圖像生成方法[J];測(cè)繪學(xué)報(bào);2010年05期

10 武曉波,王世新,肖春生;Delaunay三角網(wǎng)的生成算法研究[J];測(cè)繪學(xué)報(bào);1999年01期

相關(guān)碩士學(xué)位論文 前2條

1 戴彬;基于車載激光掃描數(shù)據(jù)的三維重建研究[D];首都師范大學(xué);2011年

2 羅東;三維模型表現(xiàn)形式轉(zhuǎn)換技術(shù)及存儲(chǔ)格式定義的研究與實(shí)現(xiàn)[D];西北大學(xué);2010年

，

本文編號(hào)：1944252