scholarly journals Novel Aerial 3D Mapping System Based on UAV Platforms and 2D Laser Scanners

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
David Roca ◽  
Joaquín Martínez-Sánchez ◽  
Susana Lagüela ◽  
Pedro Arias
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
3D Mapping ◽  
The Real ◽  
3D Point Clouds ◽  
Accuracy And Precision ◽  
Mapping System ◽  
Laser Scanners ◽  
3D Mapping System ◽  
Aerial View

The acquisition of 3D geometric data from an aerial view implies a high number of advantages with respect to terrestrial acquisition, the greatest being that aerial view allows the acquisition of information from areas with no or difficult accessibility, such as roofs and tops of trees. If the aerial platform is copter-type, other advantages are present, such as the capability of displacement at very low-speed, allowing for a more detailed acquisition. This paper presents a novel Aerial 3D Mapping System based on a copter-type platform, where a 2D laser scanner is integrated with a GNSS sensor and an IMU for the generation of georeferenced 3D point clouds. The accuracy and precision of the system are evaluated through the measurement of geometries in the point clouds generated by the system, as well as through the geolocation of target points for which the real global coordinates are known.

scholarly journals Laser-Based Obstacle Detection at Railway Level Crossings

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Vítor Amaral ◽  
Francisco Marques ◽  
André Lourenço ◽  
José Barata ◽  
Pedro Santana
Keyword(s):  
Open Problem ◽  
Laser Scanner ◽  
Point Clouds ◽  
Obstacle Detection ◽  
Background Model ◽  
Training Phase ◽  
Level Crossing ◽  
Level Crossings ◽  
3D Point Clouds ◽  
Laser Scanners

This paper presents a system for obstacle detection in railway level crossings from 3D point clouds acquired with tilting 2D laser scanners. Although large obstacles in railway level crossings are detectable with current solutions, the detection of small obstacles remains an open problem. By relying on a tilting laser scanner, the proposed system is able to acquire highly dense and accurate point clouds, enabling the detection of small obstacles, like rocks laying near the rail. During an offline training phase, the system learns a background model of the level crossing from a set of point clouds. Then, online, obstacles are detected as occupied space contrasting with the background model. To reduce the need for manual on-site calibration, the system automatically estimates the pose of the level crossing and railway with respect to the laser scanner. Experimental results show the ability of the system to successfully perform on a set of 41 point clouds acquired in an operational one-lane level crossing.

scholarly journals Panoramic Image and Three-Axis Laser Scanner Integrated Approach for Indoor 3D Mapping

2018 ◽  
Vol 10 (8) ◽  
pp. 1269 ◽  
Author(s):  
Pengcheng Zhao ◽  
Qingwu Hu ◽  
Shaohua Wang ◽  
Mingyao Ai ◽  
Qingzhou Mao
Keyword(s):  
Large Scale ◽  
Laser Scanner ◽  
Measurement Data ◽  
Point Clouds ◽  
Location Based Services ◽  
Prototype System ◽  
3D Mapping ◽  
Scenario Development ◽  
3D Point Clouds ◽  
Panoramic Images

High-precision indoor three-dimensional maps are a prerequisite for building information models, indoor location-based services, etc., but the indoor mapping solution is still in the stage of technological experiment and application scenario development. In this paper, indoor mapping equipment integrating a three-axis laser scanner and panoramic camera is designed, and the corresponding workflow and critical technologies are described. First, hardware design and software for controlling the operations and calibration of the spatial relationship between sensors are completed. Then, the trajectory of the carrier is evaluated by a simultaneous location and mapping framework, which includes reckoning of the real-time position and attitude of the carrier by a filter fusing the horizontally placed laser scanner data and inertial measurement data, as well as the global optimization by a closed-loop adjustment using a graph optimization algorithm. Finally, the 3D point clouds and panoramic images of the scene are reconstructed from two tilt-mounted laser scanners and the panoramic camera by synchronization of the position and attitude of the carrier. The experiment was carried out in a five-story library using the proposed prototype system; the results demonstrate accuracies of up to 3 cm for 2D maps, and up to 5 cm for 3D maps, and the produced point clouds and panoramic images can be utilized for modeling and further works related to large-scale indoor scenes. Therefore, the proposed system is an efficient and accurate solution for indoor 3D mapping.

scholarly journals UNCERTAINTY PROPAGATION FOR TERRESTRIAL MOBILE LASER SCANNER

2016 ◽  
Vol XLI-B3 ◽  
pp. 331-335 ◽  
Author(s):  
c Mezian ◽  
Bruno Vallet ◽  
Bahman Soheilian ◽  
Nicolas Paparoditis
Keyword(s):  
Uncertainty Analysis ◽  
Covariance Matrix ◽  
Uncertainty Propagation ◽  
Laser Scanner ◽  
Point Clouds ◽  
3D Point Clouds ◽  
Laser Scanners ◽  
Propagation Technique ◽  
The Impact

Laser scanners are used more and more in mobile mapping systems. They provide 3D point clouds that are used for object reconstruction and registration of the system. For both of those applications, uncertainty analysis of 3D points is of great interest but rarely investigated in the literature. In this paper we present a complete pipeline that takes into account all the sources of uncertainties and allows to compute a covariance matrix per 3D point. The sources of uncertainties are laser scanner, calibration of the scanner in relation to the vehicle and direct georeferencing system. We suppose that all the uncertainties follow the Gaussian law. The variances of the laser scanner measurements (two angles and one distance) are usually evaluated by the constructors. This is also the case for integrated direct georeferencing devices. Residuals of the calibration process were used to estimate the covariance matrix of the 6D transformation between scanner laser and the vehicle system. Knowing the variances of all sources of uncertainties, we applied uncertainty propagation technique to compute the variance-covariance matrix of every obtained 3D point. Such an uncertainty analysis enables to estimate the impact of different laser scanners and georeferencing devices on the quality of obtained 3D points. The obtained uncertainty values were illustrated using error ellipsoids on different datasets.

scholarly journals UNCERTAINTY PROPAGATION FOR TERRESTRIAL MOBILE LASER SCANNER

2016 ◽  
Vol XLI-B3 ◽  
pp. 331-335 ◽  
Author(s):  
c Mezian ◽  
Bruno Vallet ◽  
Bahman Soheilian ◽  
Nicolas Paparoditis
Keyword(s):  
Uncertainty Analysis ◽  
Covariance Matrix ◽  
Uncertainty Propagation ◽  
Laser Scanner ◽  
Point Clouds ◽  
3D Point Clouds ◽  
Laser Scanners ◽  
Propagation Technique ◽  
The Impact

Laser scanners are used more and more in mobile mapping systems. They provide 3D point clouds that are used for object reconstruction and registration of the system. For both of those applications, uncertainty analysis of 3D points is of great interest but rarely investigated in the literature. In this paper we present a complete pipeline that takes into account all the sources of uncertainties and allows to compute a covariance matrix per 3D point. The sources of uncertainties are laser scanner, calibration of the scanner in relation to the vehicle and direct georeferencing system. We suppose that all the uncertainties follow the Gaussian law. The variances of the laser scanner measurements (two angles and one distance) are usually evaluated by the constructors. This is also the case for integrated direct georeferencing devices. Residuals of the calibration process were used to estimate the covariance matrix of the 6D transformation between scanner laser and the vehicle system. Knowing the variances of all sources of uncertainties, we applied uncertainty propagation technique to compute the variance-covariance matrix of every obtained 3D point. Such an uncertainty analysis enables to estimate the impact of different laser scanners and georeferencing devices on the quality of obtained 3D points. The obtained uncertainty values were illustrated using error ellipsoids on different datasets.

scholarly journals 2.4 Catheter ablation of complex atrial arrhythmias with a novel 3D mapping system: The real position management

EP Europace ◽  
2003 ◽  
Vol 4 (Supplement_1) ◽  
pp. A3-A3
Author(s):  
G. Barbato ◽  
V. Carinci ◽  
F. Pergolini ◽  
A. Favaro ◽  
D. Bracchetti
Keyword(s):  
Catheter Ablation ◽  
Atrial Arrhythmias ◽  
3D Mapping ◽  
The Real ◽  
Mapping System ◽  
3D Mapping System ◽  
Position Management

scholarly journals Using Least-Squares Residuals to Assess the Stochasticity of Measurements—Example: Terrestrial Laser Scanner and Surface Modeling

2021 ◽  
Vol 5 (1) ◽  
pp. 59
Author(s):  
Gaël Kermarrec ◽  
Niklas Schild ◽  
Jan Hartmann
Keyword(s):  
Least Squares ◽  
Laser Scanner ◽  
Real Data ◽  
Point Clouds ◽  
Statistical Testing ◽  
Normal Vector ◽  
Engineering Structures ◽  
3D Point Clouds ◽  
Least Squares Adjustment ◽  
Correlation Parameters

Terrestrial laser scanners (TLS) capture a large number of 3D points rapidly, with high precision and spatial resolution. These scanners are used for applications as diverse as modeling architectural or engineering structures, but also high-resolution mapping of terrain. The noise of the observations cannot be assumed to be strictly corresponding to white noise: besides being heteroscedastic, correlations between observations are likely to appear due to the high scanning rate. Unfortunately, if the variance can sometimes be modeled based on physical or empirical considerations, the latter are more often neglected. Trustworthy knowledge is, however, mandatory to avoid the overestimation of the precision of the point cloud and, potentially, the non-detection of deformation between scans recorded at different epochs using statistical testing strategies. The TLS point clouds can be approximated with parametric surfaces, such as planes, using the Gauss–Helmert model, or the newly introduced T-splines surfaces. In both cases, the goal is to minimize the squared distance between the observations and the approximated surfaces in order to estimate parameters, such as normal vector or control points. In this contribution, we will show how the residuals of the surface approximation can be used to derive the correlation structure of the noise of the observations. We will estimate the correlation parameters using the Whittle maximum likelihood and use comparable simulations and real data to validate our methodology. Using the least-squares adjustment as a “filter of the geometry” paves the way for the determination of a correlation model for many sensors recording 3D point clouds.

scholarly journals LiDAR-Based Glass Detection for Improved Occupancy Grid Mapping

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2263
Author(s):  
Haileleol Tibebu ◽  
Jamie Roche ◽  
Varuna De Silva ◽  
Ahmet Kondoz
Keyword(s):  
Laser Scanner ◽  
Point Clouds ◽  
Light Detection And Ranging ◽  
Test Results ◽  
New Approach ◽  
Occupancy Grid ◽  
Laser Scanners ◽  
Novel Method ◽  
Occupancy Grid Mapping ◽  
Cartesian Coordinate

Creating an accurate awareness of the environment using laser scanners is a major challenge in robotics and auto industries. LiDAR (light detection and ranging) is a powerful laser scanner that provides a detailed map of the environment. However, efficient and accurate mapping of the environment is yet to be obtained, as most modern environments contain glass, which is invisible to LiDAR. In this paper, a method to effectively detect and localise glass using LiDAR sensors is proposed. This new approach is based on the variation of range measurements between neighbouring point clouds, using a two-step filter. The first filter examines the change in the standard deviation of neighbouring clouds. The second filter uses a change in distance and intensity between neighbouring pules to refine the results from the first filter and estimate the glass profile width before updating the cartesian coordinate and range measurement by the instrument. Test results demonstrate the detection and localisation of glass and the elimination of errors caused by glass in occupancy grid maps. This novel method detects frameless glass from a long range and does not depend on intensity peak with an accuracy of 96.2%.

scholarly journals Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 201
Author(s):  
Michael Bekele Maru ◽  
Donghwan Lee ◽  
Kassahun Demissie Tola ◽  
Seunghee Park
Keyword(s):  
Optical Sensors ◽  
Point Cloud ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Depth Camera ◽  
Terrestrial Laser Scanner ◽  
Cloud Data ◽  
3D Point Clouds ◽  
3D Information

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

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