Abstract

<div>The need for 3D mapping is on the rise to meet the requirements of a growing and diverse group of end-users. Existing 3D mapping systems, which have been classified according to the mode of operation as stationary, mobile and aerial, tend to serve one mode of operation only and are considered cost-prohibitive for many end-users. Unmanned aerial vehicles (UAVs) have experienced rapid growth since their introduction and their usage in 3D mapping is likewise accelerating at a rapid pace. This dissertation presents the design, development and implementation of a LiDAR-based generic 3D mapping system that can be used in the three mapping modes (stationary, mobile and UAV-based). The system provides direct georeferencing capabilities through optimized selected multimodal sensors. A fundamental part of this dissertation is the smart integration of the 3D mapping system components both on the hardware and software levels, along with a new mapping scheme that enables platform-independent deployment ability. </div><div>This research project also presents a rigorous non-linear uncertainty predictive model for the generic developed system and introduces a very low-cost variant of the system to be used in stationary and handheld mode. The developed multipurpose mapping system is tested in different environments for the three modes of operation, demonstrating its practicality, versatility and ease of deployment. To maximize the ease of deployment for diverse end-users, careful consideration is given to the mapping system components so that the developed system is ultra-lightweight, compact, and multipurpose. Additionally, this dissertation proposes a colorization workflow to make use of available optical imagery in the colorization process of the LiDAR point cloud. Lastly, the study compares two different 3D mapping approaches: 3D LiDAR-based mapping and a low-cost optical-based 3D structure from motion (SfM) workflow. The comparison is achieved by performing a real-world case study of digital surface model (DSM) generation by the two aforementioned approaches. Real-world testing that includes qualitative and quantitative validation against accurate state-of-the-art high-end LiDAR equipment proves the successful design, development and deployment of the developed crosscutting LiDAR-based 3D mapping system.</div>

Highlights

  • 1.1 BackgroundUsing maps is an integral part of our life, whether for navigation, geographic information systems, resources monitoring, surveying, or other pursuits and uses

  • The nature of producing the Digital Surface Model (DSM) and the georeferencing process is quite dissimilar to the LiDARbased developed mapping system, the structure from motion (SfM) 3D output built from matching key-points in optical imagery, and the Polaris dataset that has been captured with a terrestrial point of view

  • The main focus of the research presented was the development of a generic framework for a multipurpose, platform-independent, Light Detection And Ranging (LiDAR)-based mapping system

Read more

Summary

A CROSSCUTTING THREE-MODES-OF-OPERATION UNIQUE LiDAR-BASED 3D MAPPING SYSTEM

GENERIC FRAMEWORK ARCHITECTURE, UNCERTAINTY PREDICTIVE MODEL AND SfM AUGMENTATION by Ashraf Mohamed Abdelaziz Elshorbagy B.Sc., Cairo University, Egypt, 2000. I hereby declare that I am the sole author of this dissertation. This is a true copy of the dissertation, including any required final revisions, as accepted by my examiners. I authorize Ryerson University to lend this dissertation to other institutions or individuals for the purpose of scholarly research. I further authorize Ryerson University to reproduce this dissertation by photocopying or by other means, in total or in part, at the request of other institutions or individuals for the purpose of scholarly research. I understand that my dissertation may be made electronically available to the public

Background
Motivation
Problem Statement and Research Challenges
Research Objectives
Dissertation Outline This dissertation is organized as follows
Overview
LiDAR Data Generation
LiDAR-based Mapping Systems
Structure from Motion SfM Photogrammetry
LiDAR and Optical imagery data Fusion
DSM and DEM generation Approaches
Introduction
Optimized Selection of Sensors
LiDAR RSS optimized selection LiDAR scanners are active RSS sensors
GNSS/INS optimized selection
System Management Unit SMU optimized selection
Mapping system building blocks Signal Synchronization
Mapping system Components’ EMI
Mapping System Building Block Data Fusion
Data processing of GNSS and IMU data
Preparation of LIDAR data
Interpolation and joining with synchronized time-stamps
VLP-16 Data Capture Mechanism
Mobile mapping Setup
UAV mapping Setup
System Uncertainty Predictive Model
Data Collection in Stationary Mode (LiDAR)
Data Collection in Stationary Mode (Optical Imagery)
System in Handheld Mode
MMS Tilted Orientation
LiDAR data collection
Optical Data collection
Captured Data Analysis (SfM)
Summary and Conclusions
Generic framework of the system
System realization (Stationary mode)
System realization (MMS mode)
System realization (ULS mode)
SfM and ULS DSM generation
Findings
Recommendations for future work
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.