scholarly journals PORTABLE IMAGE-BASED HIGH PERFORMANCE MOBILE MAPPING SYSTEM IN UNDERGROUND ENVIRONMENTS – SYSTEM CONFIGURATION AND PERFORMANCE EVALUATION

2019 ◽  
Vol IV-2/W5 ◽  
pp. 255-262
Author(s):  
S. Blaser ◽  
S. Nebiker ◽  
D. Wisler
Keyword(s):  
High Performance ◽  
Life Cycle Management ◽  
Measurement Unit ◽  
Indoor Environments ◽  
Mobile Mapping ◽  
Mapping System ◽  
Order Of Magnitude ◽  
Mobile Mapping System ◽  
And Performance ◽  
Measurement Campaigns

<p><strong>Abstract.</strong> The progression in urbanization increases the need for different types of underground infrastructure. Consequently, infrastructure and life cycle management are rapidly gaining in importance. Mobile reality capturing systems and cloud-based services exploiting georeferenced metric 3D imagery are already extensively used for infrastructure management in outdoor environments. These services minimise dangerous and expensive field visits or measurement campaigns. In this paper, we introduce the BIMAGE Backpack, a portable image-based mobile mapping system for 3D data acquisition in indoor environments. The system consists of a multi-head panorama camera, two multi-profile laser scanners and an inertial measurement unit. With this system, we carried out underground measurement campaigns in the Hagerbach Test Gallery, located in Flums Hochwiese, Switzerland. For our performance evaluations in two different tunnel sections, we employed LiDAR SLAM as well as advanced image-based georeferencing. The obtained absolute accuracies were in the range from 6.2 to 7.4&amp;thinsp;cm. The relative accuracy, which for many applications is even more important, was in the range of 2&amp;ndash;6&amp;thinsp;mm. These figures demonstrate an accuracy improvement of the subsequent image-based georeferencing over LiDAR SLAM by about an order of magnitude. The investigations show the application potential of image-based portable mobile mapping systems for infrastructure inventory and management in large underground facilities.</p>

scholarly journals SYSTEM DESIGN, CALIBRATION AND PERFORMANCE ANALYSIS OF A NOVEL 360° STEREO PANORAMIC MOBILE MAPPING SYSTEM

2017 ◽  
Vol IV-1/W1 ◽  
pp. 207-213
Author(s):  
S. Blaser ◽  
S. Nebiker ◽  
S. Cavegn
Keyword(s):  
Calibration Procedure ◽  
Mobile Mapping ◽  
Camera Systems ◽  
3D City Model ◽  
Mapping System ◽  
Mobile Mapping System ◽  
City Model ◽  
And Performance ◽  
Mobile Mapping Systems ◽  
Street Environment

Image-based mobile mapping systems enable the efficient acquisition of georeferenced image sequences, which can later be exploited in cloud-based 3D geoinformation services. In order to provide a 360° coverage with accurate 3D measuring capabilities, we present a novel 360° stereo panoramic camera configuration. By using two 360° panorama cameras tilted forward and backward in combination with conventional forward and backward looking stereo camera systems, we achieve a full 360° multi-stereo coverage. We furthermore developed a fully operational new mobile mapping system based on our proposed approach, which fulfils our high accuracy requirements. We successfully implemented a rigorous sensor and system calibration procedure, which allows calibrating all stereo systems with a superior accuracy compared to that of previous work. Our study delivered absolute 3D point accuracies in the range of 4 to 6 cm and relative accuracies of 3D distances in the range of 1 to 3 cm. These results were achieved in a challenging urban area. Furthermore, we automatically reconstructed a 3D city model of our study area by employing all captured and georeferenced mobile mapping imagery. The result is a very high detailed and almost complete 3D city model of the street environment.

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 Nighttime Mobile Laser Scanning and 3D Luminance Measurement: Verifying the Outcome of Roadside Tree Pruning with Mobile Measurement of the Road Environment

2020 ◽  
Vol 9 (7) ◽  
pp. 455
Author(s):  
Mikko Maksimainen ◽  
Matti T. Vaaja ◽  
Matti Kurkela ◽  
Juho-Pekka Virtanen ◽  
Arttu Julin ◽  
...  
Keyword(s):  
Measurement System ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Measurement Unit ◽  
Mobile Mapping ◽  
Camera System ◽  
Roadside Vegetation ◽  
Mapping System ◽  
Mobile Mapping System ◽  
The Difference

Roadside vegetation can affect the performance of installed road lighting. We demonstrate a workflow in which a car-mounted measurement system is used to assess the light-obstructing effect of roadside vegetation. The mobile mapping system (MMS) includes a panoramic camera system, laser scanner, inertial measurement unit, and satellite positioning system. The workflow and the measurement system were applied to a road section of Munkkiniemenranta, Helsinki, Finland, in 2015 and 2019. The relative luminance distribution on a road surface and the obstructing vegetation were measured before and after roadside vegetation pruning applying a luminance-calibrated mobile mapping system. The difference between the two measurements is presented, and the opportunities provided by the mobile 3D luminance measurement system are discussed.

scholarly journals THE PERFORMANCE ANALYSIS OF AN INDOOR MOBILE MAPPING SYSTEM WITH RGB-D SENSOR

2015 ◽  
Vol XL-1/W4 ◽  
pp. 183-188
Author(s):  
G. J. Tsai ◽  
K. W. Chiang ◽  
C. H. Chu ◽  
Y. L. Chen ◽  
N. El-Sheimy ◽  
...  
Keyword(s):  
Low Cost ◽  
Measurement Unit ◽  
Floor Plan ◽  
Mobile Mapping ◽  
Validation And Verification ◽  
Localization And Mapping ◽  
Mapping System ◽  
Mapping Technology ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems

Over the years, Mobile Mapping Systems (MMSs) have been widely applied to urban mapping, path management and monitoring and cyber city, etc. The key concept of mobile mapping is based on positioning technology and photogrammetry. In order to achieve the integration, multi-sensor integrated mapping technology has clearly established. In recent years, the robotic technology has been rapidly developed. The other mapping technology that is on the basis of low-cost sensor has generally used in robotic system, it is known as the Simultaneous Localization and Mapping (SLAM). The objective of this study is developed a prototype of indoor MMS for mobile mapping applications, especially to reduce the costs and enhance the efficiency of data collection and validation of direct georeferenced (DG) performance. The proposed indoor MMS is composed of a tactical grade Inertial Measurement Unit (IMU), the Kinect RGB-D sensor and light detection, ranging (LIDAR) and robot. In summary, this paper designs the payload for indoor MMS to generate the floor plan. In first session, it concentrates on comparing the different positioning algorithms in the indoor environment. Next, the indoor plans are generated by two sensors, Kinect RGB-D sensor LIDAR on robot. Moreover, the generated floor plan will compare with the known plan for both validation and verification.

A Mobile Mapping System for Precise Road Line Localization Using a Single Camera and 3D Road Model

2007 ◽  
Vol 19 (2) ◽  
pp. 174-180 ◽  
Author(s):  
Kiichiro Ishikawa ◽  
◽  
Yoshiharu Amano ◽  
Takumi Hashizume ◽  
Jun-ichi Takiguchi ◽  
...  
Keyword(s):  
Navigation System ◽  
Dead Reckoning ◽  
Driving Safety ◽  
Measurement Unit ◽  
Surface Model ◽  
Center Line ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Highway Alignment

Precise highway alignment data to be used in car navigation and ITS to increase driving safety must be kept up-to-date and accurate. A Mobile Mapping System (MMS) provides a highway alignment database and offers unparalleled productivity when combined with navigation and videogrammetry tools. The MMS we propose features a GPS/Dead Reckoning (DR) combined navigation system, a three-axis GPS-Gyro/Inertial Measurement Unit (IMU), laser scanners, nearly horizontal cameras, and network-based Positioning Augmentation Services (PASTM) (Mitsubishi Electric Corporation) and measures center-line and side-line locations precisely based on a 3D road surface model. The carrier-phased D-GPS/DR navigation system and GPS-Gyro/IMU conducts highly accurate positioning in centimeters and posture estimation at 0.073° rms for heading, 0.064° rms for pitch, and 0.116° for roll. It provides 0.095 m rms accuracy for both center-line and side-line measurement when GPS visibility is sufficient. A comparison of accuracy between static RTK-GPS measurement and MMS measurement on the Tateyama Kurobe alpine route confirmed MMS dynamic measurement accuracy and effectiveness.

Pavement Distress and Debris Detection using a Mobile Mapping System with 2D Profiler LiDAR

2021 ◽  
pp. 036119812110025
Author(s):  
Radhika Ravi ◽  
Darcy Bullock ◽  
Ayman Habib
Keyword(s):  
Validation Dataset ◽  
Public Agencies ◽  
Work Zones ◽  
Mobile Mapping ◽  
Pavement Distress ◽  
Mapping System ◽  
Pavement Monitoring ◽  
Order Of Magnitude ◽  
Mobile Mapping System ◽  
Mobile Mapping Systems

Regular pavement monitoring over highways and airport runways is vital for public agencies to ensure the safe riding of vehicles and aircrafts. Highways are mostly subject to cracking and potholes along with a few instances of debris around construction work zones. Airports are also concerned with debris but have much lower tolerance for the presence of foreign object debris (FOD) that could possibly damage the aircraft. LiDAR is rapidly emerging in a variety of mobile mapping systems (MMS) and will likely be integrated into many transportation vehicles over the next decade for pavement inspection. This paper proposes a unique algorithm for pavement surface inspection with the help of MMS driven at highway speeds. The study analyzed LiDAR data acquired for 8 mi of highway collected at approximately 55 to 60 mph. This study indicates that an adequately designed MMS along with the proposed algorithm can efficiently detect pavement anomalies as small as 2 cm in the form of cracking, potholes, surface debris, or any combination of these. This is more than sufficient for highways, where debris such as ladders and tires are an order of magnitude larger. For evaluating the effectiveness of detecting smaller airport FOD, a validation dataset was created by driving the MMS at 15 mph adjacent to a debris field of 50 sample pieces of FOD collected from an airport. The study found that 100% of the FOD items larger than 2 cm in size (12 out of 50 samples) were detected successfully at 15 mph. Both datasets suggest that MMS LiDAR is sufficient for pavement inspection and as sensor fidelity increases, even small FOD will be able to be detected with the algorithm proposed in this paper.

scholarly journals Deep Learning Based Pavement Inspection Using Self-Reconfigurable Robot

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2595
Author(s):  
Balakrishnan Ramalingam ◽  
Abdullah Aamir Hayat ◽  
Mohan Rajesh Elara ◽  
Braulio Félix Gómez ◽  
Lim Yi ◽  
...  
Keyword(s):  
Deep Learning ◽  
Semantic Segmentation ◽  
High Accuracy ◽  
Experimental Results ◽  
Mobile Mapping ◽  
Mapping System ◽  
Mobile Mapping System ◽  
Reconfigurable Robot ◽  
Nvidia Gpu ◽  
Inspection Task

The pavement inspection task, which mainly includes crack and garbage detection, is essential and carried out frequently. The human-based or dedicated system approach for inspection can be easily carried out by integrating with the pavement sweeping machines. This work proposes a deep learning-based pavement inspection framework for self-reconfigurable robot named Panthera. Semantic segmentation framework SegNet was adopted to segment the pavement region from other objects. Deep Convolutional Neural Network (DCNN) based object detection is used to detect and localize pavement defects and garbage. Furthermore, Mobile Mapping System (MMS) was adopted for the geotagging of the defects. The proposed system was implemented and tested with the Panthera robot having NVIDIA GPU cards. The experimental results showed that the proposed technique identifies the pavement defects and litters or garbage detection with high accuracy. The experimental results on the crack and garbage detection are presented. It is found that the proposed technique is suitable for deployment in real-time for garbage detection and, eventually, sweeping or cleaning tasks.

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