3D map building method with mobile mapping system in indoor environments

Author(s):  
Yu-Cheol Lee ◽  
Seung-Hwan Park
Author(s):  
H. A. Lauterbach ◽  
D. Borrmann ◽  
A. Nüchter ◽  
A. P. Rossi ◽  
V. Unnithan ◽  
...  

<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>


Author(s):  
S. Blaser ◽  
S. Nebiker ◽  
D. Wisler

<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>


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2595
Author(s):  
Balakrishnan Ramalingam ◽  
Abdullah Aamir Hayat ◽  
Mohan Rajesh Elara ◽  
Braulio Félix Gómez ◽  
Lim Yi ◽  
...  

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.


Author(s):  
Kiichiro Ishikawa ◽  
Jun-ichi Takiguchi ◽  
Yoshiharu Amano ◽  
Takumi Hashizume

Author(s):  
Nicolas Paparoditis ◽  
Jean-Pierre Papelard ◽  
Bertrand Cannelle ◽  
Alexandre Devaux ◽  
Bahman Soheilian ◽  
...  

Nous présentons dans cet article un système de numérisation mobile 3D hybride laser-image qui permet d'acquérir des infrastructures de données spatiales répondant aux besoins d'applications diverses allant de navigations multimédia immersives jusqu'à de la métrologie 3D à travers le web. Nous détaillons la conception du système, ses capteurs, son architecture et sa calibration, ainsi qu'un service web offrant la possibilité de saisir en 3D via un outil de type SaaS (Software as a Service), permettant à tout un chacun d'enrichir ses propres bases de données à hauteur de ses besoins.Nous abordons également l'anonymisation des données, à savoir la détection et le floutage de plaques d'immatriculation, qui est est une étape inévitable pour la diffusion de ces données sur Internet via des applications grand public.


Sign in / Sign up

Export Citation Format

Share Document