scholarly journals MONITORING CAPABILITIES OF A MOBILE MAPPING SYSTEM BASED ON NAVIGATION QUALITIES

2016 ◽  
Vol XLI-B1 ◽  
pp. 625-631
Author(s):  
H. Jing ◽  
N. Slatcher ◽  
X. Meng ◽  
G. Hunter
Keyword(s):  
Change Detection ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Mapping System ◽  
Short Period ◽  
Laser Scanners ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Mobile mapping systems are becoming increasingly popular as they can build 3D models of the environment rapidly by using a laser scanner that is integrated with a navigation system. 3D mobile mapping has been widely used for applications such as 3D city modelling and mapping of the scanned environments. However, accurate mapping relies on not only the scanner’s performance but also on the quality of the navigation results (accuracy and robustness) . This paper discusses the potentials of using 3D mobile mapping systems for landscape change detection, that is traditionally carried out by terrestrial laser scanners that can be accurately geo-referenced at a static location to produce highly accurate dense point clouds. Yet compared to conventional surveying using terrestrial laser scanners, several advantages of mobile mapping systems can be identified. A large area can be monitored in a relatively short period, which enables high repeat frequency monitoring without having to set-up dedicated stations. However, current mobile mapping applications are limited by the quality of navigation results, especially in different environments. The change detection ability of mobile mapping systems is therefore significantly affected by the quality of the navigation results. This paper presents some data collected for the purpose of monitoring from a mobile platform. The datasets are analysed to address current potentials and difficulties. The change detection results are also presented based on the collected dataset. Results indicate the potentials of change detection using a mobile mapping system and suggestions to enhance quality and robustness.

scholarly journals MONITORING CAPABILITIES OF A MOBILE MAPPING SYSTEM BASED ON NAVIGATION QUALITIES

2016 ◽  
Vol XLI-B1 ◽  
pp. 625-631 ◽  
Author(s):  
H. Jing ◽  
N. Slatcher ◽  
X. Meng ◽  
G. Hunter
Keyword(s):  
Change Detection ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Mapping System ◽  
Short Period ◽  
Laser Scanners ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Mobile mapping systems are becoming increasingly popular as they can build 3D models of the environment rapidly by using a laser scanner that is integrated with a navigation system. 3D mobile mapping has been widely used for applications such as 3D city modelling and mapping of the scanned environments. However, accurate mapping relies on not only the scanner’s performance but also on the quality of the navigation results (accuracy and robustness) . This paper discusses the potentials of using 3D mobile mapping systems for landscape change detection, that is traditionally carried out by terrestrial laser scanners that can be accurately geo-referenced at a static location to produce highly accurate dense point clouds. Yet compared to conventional surveying using terrestrial laser scanners, several advantages of mobile mapping systems can be identified. A large area can be monitored in a relatively short period, which enables high repeat frequency monitoring without having to set-up dedicated stations. However, current mobile mapping applications are limited by the quality of navigation results, especially in different environments. The change detection ability of mobile mapping systems is therefore significantly affected by the quality of the navigation results. This paper presents some data collected for the purpose of monitoring from a mobile platform. The datasets are analysed to address current potentials and difficulties. The change detection results are also presented based on the collected dataset. Results indicate the potentials of change detection using a mobile mapping system and suggestions to enhance quality and robustness.

scholarly journals MOBILE MAPPING OF THE LA CORONA LAVATUBE ON LANZAROTE

2019 ◽  
Vol IV-2/W5 ◽  
pp. 381-387 ◽  
Author(s):  
H. A. Lauterbach ◽  
D. Borrmann ◽  
A. Nüchter ◽  
A. P. Rossi ◽  
V. Unnithan ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Optimization Approach ◽  
Indoor Environments ◽  
Mobile Mapping ◽  
Trajectory Estimation ◽  
Mapping System ◽  
Laser Scanners ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

<p><strong>Abstract.</strong> Planetary surfaces consist of rough terrain and cave-like environments. Future planetary exploration demands for accurate mapping. However, recent backpack mobile mapping systems are mostly tested in structured, indoor environments. This paper evaluates the use of a backpack mobile mapping system in a cave-like environment. The experiments demonstrate the abilities of an continuous-time optimization approach by mapping part of a lavatube of the La Corona volcano system on Lanzarote. We compare two strategies for trajectory estimation relying either on 2D or 3D laser scanners and show that a 3D laser scanner substantially improved the final results.</p>

scholarly journals Performance Assessment of Mobile Laser Scanning Systems Using Velodyne Hdl-32e

2021 ◽  
Vol 1 (1) ◽  
pp. 28-33
Author(s):  
Bashar Alsadik
Keyword(s):  
Laser Scanning ◽  
Impact Analysis ◽  
Orientation Angle ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Ongoing Research ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Mapping systems using multi-beam LiDARs are widely used nowadays for different geospatial applications graduating from indoor projects to outdoor city-wide projects. These mobile mapping systems can be either ground-based or aerial-based systems and are mostly equipped with inertial navigation systems INS. The Velodyne HDL-32 LiDAR is a well-known 360° spinning multi-beam laser scanner that is widely used in outdoor and indoor mobile mapping systems. The performance of such LiDARs is an ongoing research topic which is quite important for the quality assurance and quality control topic. The performance of this LiDAR type is correlated to many factors either related to the device itself or the design of the mobile mapping system. Regarding design, most of the mapping systems are equipped with a single Velodyne HDL32 in a specific orientation angle which is different among the mapping systems manufacturers. The LiDAR orientation angle has a significant impact on the performance in terms of the density and coverage of the produced point clouds. Furthermore, during the lifetime of this multi-beam LiDAR, one or more beams may be defected and then either continue the production or returned to the manufacturer to be fixed which then cost time and money. In this paper, the design impact analysis of a mobile laser scanning (MLS) system equipped with a single Velodyne HDL-32E will be clarified and a clear relationship is given between the orientation angle of the LiDAR and the output density of points. The ideal angular orientation of a single Velodyne HDL-32E is found to be at 35° in a mobile mapping system. Furthermore, we investigated the degradation of points density when one of the 32 beams is defected and quantified the density loss percentage and to the best of our knowledge, this is not presented in literature before. It is found that a maximum of about 8% point density loss occurs on the ground and 4% on the facades when having a defected beam of the Velodyne HDL-32E.   

Pothole Mapping and Patching Quantity Estimates using LiDAR-Based Mobile Mapping Systems

2020 ◽  
Vol 2674 (9) ◽  
pp. 124-134
Author(s):  
Radhika Ravi ◽  
Ayman Habib ◽  
Darcy Bullock
Keyword(s):  
Point Clouds ◽  
Relative Accuracy ◽  
Mobile Mapping ◽  
Cloud Data ◽  
Pavement Distress ◽  
The Road ◽  
Mapping System ◽  
Mobile Mapping System ◽  
The Cost ◽  
Mapping Systems

Pavement distress or pothole mapping is important to public agencies responsible for maintaining roadways. The efficient capture of 3D point cloud data using mapping systems equipped with LiDAR eliminates the time-consuming and labor-intensive manual classification and quantity estimates. This paper proposes a methodology to map potholes along the road surface using ultra-high accuracy LiDAR units onboard a wheel-based mobile mapping system. LiDAR point clouds are processed to detect and report the location and severity of potholes by identifying the below-road 3D points pertaining to potholes, along with their depths. The surface area and volume of each detected pothole is also estimated along with the volume of its minimum bounding box to serve as an aide to choose the ideal method of repair as well as to estimate the cost of repair. The proposed approach was tested on a 10 mi-long segment on a U.S. Highway and it is observed to accurately detect potholes with varying severity and different causes. A sample of potholes detected in a 1 mi segment has been reported in the experimental results of this paper. The point clouds generated using the system are observed to have a single-track relative accuracy of less than ±1 cm and a multi-track relative accuracy of ±1–2 cm, which has been verified through comparing point clouds captured by different sensors from different tracks.

scholarly journals Test Charts for Evaluating Imaging and Point Cloud Quality of Mobile Mapping Systems for Urban Street Space Acquisition

2021 ◽  
Vol 13 (2) ◽  
pp. 237
Author(s):  
Norbert Pfeifer ◽  
Johannes Falkner ◽  
Andreas Bayr ◽  
Lothar Eysn ◽  
Camillo Ressl
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Practical Method ◽  
Image Resolution ◽  
Test Method ◽  
Mobile Mapping ◽  
Point Distribution ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Mobile mapping is in the process of becoming a routinely applied standard tool to support administration of cities. For ensuring the usability of the mobile mapping data it is necessary to have a practical method to evaluate the quality of different systems, which reaches beyond 3D accuracy of individual points. Such a method must be objective, easy to implement, and provide quantitative results to be used in tendering processes. We present such an approach which extracts quality figures for point density, point distribution, point cloud planarity, image resolution, and street sign legibility. In its practical application for the mobile mapping campaign of the City of Vienna (Austria) in 2020 the proposed test method proved to fulfill the above requirements. As an additional result, quality figures are reported for the panorama images and point clouds of three different mobile mapping systems.

scholarly journals INDOOR BUILDING SURVEY ASSESSMENT

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 251-257
Author(s):  
T. Lovas ◽  
K. Hadzijanisz ◽  
V. Papp ◽  
A. J. Somogyi
Keyword(s):  
Point Clouds ◽  
Mobile Mapping ◽  
Localization And Mapping ◽  
Resource Needs ◽  
Land Surveying ◽  
Laser Scanners ◽  
Mapping Technology ◽  
Application Fields ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Abstract. There are multiple emerging technologies, devices and integrated equipment to support indoor mapping. The two main categories are the wearable/portable (e.g. hand-held or backpack devices) and the trolley based devices. The most widely used sensors of the integrated systems are the laser scanners (usually profile scanners), camera(s) and the IMU unit. Compared to outdoor mobile mapping systems the main difference is the lack of GNSS signals; localization is usually supported by SLAM (Simultaneous Localization and Mapping) technology, using Kalman-filtering. Current paper discusses the assessment of the potential of trolley-based indoor mobile mapping systems (MMS) by surveying a building part by multiple technologies. Besides conventional land surveying measurements, terrestrial lasers scanning and a backpack-based mobile survey have been carried out. The analysis included cloud-to-cloud comparison as well as CAD-based evaluation focusing on the geometric accuracy of the point clouds. The paper also presents the surveying workflow; on its resource-needs and potential application fields. The paper discusses the data acquisition technologies and procedures and the different quality assessment methods and results. Since an experimental survey was conducted with a backpack-based unit in the same study area, the paper gives a brief overview on how the two different mobile mapping technologies can be applied indoor, and presents the main differences, advantages and drawbacks.

scholarly journals THEORETICAL ACCURACY PREDICTION AND VALIDATION OF LOW-END AND HIGH-END MOBILE MAPPING SYSTEM IN URBAN, RESIDENTIAL AND RURAL AREAS

2019 ◽  
Vol XLII-2/W18 ◽  
pp. 121-128 ◽  
Author(s):  
L. Mattheuwsen ◽  
M. Bassier ◽  
M. Vergauwen
Keyword(s):  
Rural Areas ◽  
Mobile Mapping ◽  
Major Drawback ◽  
Mapping System ◽  
Accuracy Level ◽  
Mobile Mapping System ◽  
3D Information ◽  
Mobile Mapping Systems ◽  
Theoretical Accuracy ◽  
Mapping Systems

Abstract. Mobile mapping systems are increasingly being used for the acquisition of 3D information of the environment. Although these systems are very efficient in data capturing compared to more traditional methods, the high cost of high-end accurate mobile mapping systems is a major drawback. In contrast, the much cheaper low-end mobile mapping systems are more frequently used for less accurate projects where visualization is more important. In general, the achievable accuracy level is the driving factor that differentiates low-end from high-end systems. To determine this value, the sensor quality, calibration and GNSS reception quality should be reliably evaluated.In this paper, we present a theoretical accuracy model of a mobile mapping system that takes into account variable GNSS accuracy. The predicted accuracy level of low-end and high-end mobile mapping systems is evaluated in a comprehensive accuracy analysis. The absolute accuracy of the system is determined in three datasets in which GNSS reception quality varies between optimal, good and poor. Additionally, the relative accuracy of both systems is checked by comparison of control distances. The presented approach allows for a more general and robust accuracy prediction of mobile mapping systems in different circumstances.

scholarly journals Extraction of Guardrails from MMS Data Using Convolutional Neural Network

2021 ◽  
Vol 15 (3) ◽  
pp. 258-267
Author(s):  
Hiroki Matsumoto ◽  
◽  
Yuma Mori ◽  
Hiroshi Masuda
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Asset Management ◽  
Extraction Method ◽  
Point Clouds ◽  
Mobile Mapping ◽  
Method Point ◽  
Mobile Mapping Systems ◽  
Capture Point ◽  
Mapping Systems

Mobile mapping systems can capture point clouds and digital images of roadside objects. Such data are useful for maintenance, asset management, and 3D map creation. In this paper, we discuss methods for extracting guardrails that separate roadways and walkways. Since there are various shape patterns for guardrails in Japan, flexible methods are required for extracting them. We propose a new extraction method based on point processing and a convolutional neural network (CNN). In our method, point clouds and images are segmented into small fragments, and their features are extracted using CNNs for images and point clouds. Then, features from images and point clouds are combined and investigated using whether they are guardrails or not. Based on our experiments, our method could extract guardrails from point clouds with a high success rate.

scholarly journals CLASSIFICATION OF RAILWAY ASSETS IN MOBILE MAPPING POINT CLOUDS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 219-225
Author(s):  
M. Corongiu ◽  
A. Masiero ◽  
G. Tucci
Keyword(s):  
Spatial Information ◽  
Point Clouds ◽  
Railway Track ◽  
Neural Net ◽  
Mobile Mapping ◽  
Geospatial Information ◽  
Railway System ◽  
Point Neighborhood ◽  
Mobile Mapping Systems ◽  
Mapping Systems

Abstract. Nowadays, mobile mapping systems are widely used to quickly collect reliable geospatial information of relatively large areas: thanks to such characteristics, the number of applications and fields exploiting their usage is continuously increasing. Among such possible applications, mobile mapping systems have been recently considered also by railway system managers to quickly produce and update a database of the geospatial features of such system, also called assets. Despite several vehicles, devices and acquisition methods can be considered for the data collection of the railway system, the predominant one is probably that based on the use of a mobile mapping system mounted on a train, which moves all along the railway tracks, enabling the 3D reproduction of the entire railway track area.Given the large amount of data collected by such mobile mapping, automatic procedures have to be used to speed up the process of extracting the spatial information of interest, i.e. assets positions and characteristics.This paper considers the problem of extracting such information for what concerns cantilever and portal masts, by exploiting a mixed approach. First, a set of candidate areas are extracted and pre-processed by considering certain of their geometric characteristics, mainly extracted by using eigenvalues of the covariance matrix of a point neighborhood. Then, a 3D modified Fisher vector-deep learning neural net is used to classify the candidates. Tests on such approach are conducted in two areas of the Italian railway system.

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