Model building for simulation and testing under uncertain conditions (original) (raw)
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Mobile scanning system for the fast digitization of existing roadways and structures
Sensor Review - SENS REV, 2006
Purpose – To present a Mobile Scanning System for digitizing three-dimensional (3D) models of real-world terrain. Design/methodology/approach – A combination of sensors (video, laser range, positioning, orientation) is placed on a mobile platform, which moves past the scene to be digitized. Data fusion from the sensors is performed to construct an accurate D model of the target environment. Findings – The developed system can acquire accurate models of real-world environments in real time, at resolutions suitable for a variety of tasks. Originality/value – Treating the individual subsystems of the mobile scanning system independently yields a robust system that can be easily reconfigured on the fly for a variety of scanning scenarios.
2013
The aim of this paper is to provide the reader with an accurate description of all the steps and procedures needed to use a Laser Scanner as suitable tool for creating 3D models from real objects/environments. By following the steps and procedures described in the paper it is possible to carry out a physical survey of the object being modeled, create a mapping assessment in term of object measurement, execute in a simple and quick way the scanning activity (also in a limited time), use the 3D model for Virtual and Constructive simulations.
A Multi-Resolution Approach for an Automated Fusion of Different Low-Cost 3D Sensors
Sensors, 2014
The 3D acquisition of object structures has become a common technique in many fields of work, e.g., industrial quality management, cultural heritage or crime scene documentation. The requirements on the measuring devices are versatile, because spacious scenes have to be imaged with a high level of detail for selected objects. Thus, the used measuring systems are expensive and require an experienced operator. With the rise of low-cost 3D imaging systems, their integration into the digital documentation process is possible. However, common low-cost sensors have the limitation of a trade-off between range and accuracy, providing either a low resolution of single objects or a limited imaging field. Therefore, the use of multiple sensors is desirable. We show the combined use of two low-cost sensors, the Microsoft Kinect and the David laserscanning system, to achieve low-resolved scans of the whole scene and a high level of detail for selected objects, respectively. Afterwards, the high-resolved David objects are automatically assigned to their corresponding Kinect object by the use of surface feature histograms and SVM-classification. The corresponding objects are fitted using an ICP-implementation to produce a multi-resolution map. The applicability is shown for a fictional crime scene and the reconstruction of a ballistic trajectory.
2011
A 3D laser scanner is an active image capturing instrument that has the ability to accurately send a signal and capture it back in x, y and z dimension. The then can be used to produce the real surface condition in relevant processing software which is suitable for direct measurement on the image or constructing DTM (Digital Terrain Model) the as what is possible in photogrammetry. A 3D laser scanner captured image the same as photogrammetric camera that capture x and y coordinates and z value measured by distance from the instrument to the object. As the development of computer technology become so advanced the capability of software to handle images captured with certain overlapping coverage to produced 3D model has been proven capable of producing a high quality surface model as the raw data captured in 3D with instrument coordinates system. The principal used in laser scanning technology is the same in photogrammetry but the different is the laser scanner can measure distance from the object to the centre of the instrument as well as it offer a different scanning resolution and wider angle of coverage which is not available in normal camera used in close range photogrammetry. When the laser scanner scan a object it actually calculate the a 3 dimensional coordinate for each pixel on the object based on the principal of 3D triangulation since it measure distance, angle and high of instrument provided by user. A surveying technique for acquiring positional data to construct DTM (Digital Terrain Model) such as laser scanner should be evaluate the impact of scanning resolution in order to relate the scanning resolution and the accuracy of the surface model for a GIS or any other application. The technique of producing 3D model and the size of spatial pixel captured during observation must relevant to the cost of producing and accuracy requirement of the client. This paper will study the impact of scanning resolution on the accuracy of the points on the ground by com- aring the coordinate obtained with 3D scanner with GPS static observation.
Sensor fusion for creating a three-dimensional model for mobile robot navigation
International Journal of Advanced Robotic Systems
This article deals with the design of an automated system for creating a three-dimensional model of the environment with its texture. The method for creating a three-dimensional model of the environment is based on the use of a two-dimensional scanner for which the supporting hardware has been designed and constructed. The whole system extends the use of a two-dimensional scanner that is embedded in a robotic system. Supporting hardware rotates the scanner around the scan axis. This will create a three-dimensional model of the environment using a two-dimensional scanner. Thus, the resulting three-dimensional scan is formed by subsequent two-dimensional scans, each shifted with respect to the previous one. It was necessary to design the appropriate software for hardware management to control the movement of the engine, the scanner, and to process the measured data. The proposed system can be placed on various exploration robotic systems that map the space using the proposed method. W...
Construction of digital surface model by multi-sensor integration from an unmanned helicopter
2004
Three dimensional data is in great demand for the various applications. In order to represent 3D space in details, it is indispensable to acquire 3D shape and texture together efficiently. However, there still lack a reliable, quick, cheap and handy method of acquiring three dimensional data of objects at higher resolution and accuracy in outdoor and moving environments. In this research, we propose a combination of a digital camera and a small (cheap) laser scanner with inexpensive IMU and GPS for an unmanned helicopter. Direct geo-referencing is achieved automatically using all the sensors without any ground control points. After the accurate trajectory of the platform with attitude changes are determined through the direct geo-referencing, 3D shape of objects is determined by laser scanner as 3D point cloud data, while texture is acquired by CCD sensor from the same platform simultaneously. A method of direct geo-referencing of range data and CCD images by integrating multi sensors for constructing digital surface model are focused. While measuring, an unmanned helicopter is continuously changing its position and attitude with respect to time. For direct geo-referencing, IMU measures the movement of the platform. IMU has a rising quality, but it is still affected by systematic errors. Through Kalman filter operation, an optimal estimate of the sensor position and attitude are determined from GPS and IMU. Meanwhile, geo-referencing of CCD image is determined by bundle block adjustment. GPS and IMU allow automatic setting of tie-points and they reduce the number of tie-points and searching time of tie-points by limiting of searching area. The result of bundle block adjustment aids Kalman filter. IMU are initialized for Kalman filter using the result of bundle block adjustment. That is, after every bundle block adjustment, IMU and its error are complemented. Geo-referencing of laser range data is done by using the result of aiding Kalman filter. Therefore, geo-referencing of range data and CCD images is done directly to overlap exactly with high accuracy and high resolution. The method of data acquisition and digital surface modelling is developed by direct geo-referencing of laser range data and CCD images with GPS and IMU. This is the way of rendering objects with rich shape and detailed texture automatically. A new method of direct geo-referencing by the combination of bundle block adjustment and Kalman filter is proposed.
Combination of Multisensor 3D Data with Error Bounds
This paper address the steps associated to re-construct a model based on a number of scans acquired with different sensor techniques. It discusses the concept of managing and operating on scans with different origins, which may have different spatial resolution, accuracy and coverage. In order to cope with these varying sensor characteristics, it introduces the concept of error-bound to all points. This error-bound describes the uncertainty with which further operations on the point need to be considered. Furthermore, the paper discusses the concepts of modified registration and fusion/integration using the error-bound concept in order to achieve the best possible model based on the inserted scans. The technique described in the paper has been applied to a reconstruction project for parts of the city centre of Verona, Italy.
A comparison of systems and tools for 3D scanning
2005
ABSTRACT: Many 3D scanning systems and software tools are currently available, but a comparative study of their actual precision and robustness still lacks. To this end, this paper presents a comparison of three alignment tools and two merging tools that were used during the reconstruction of a 3D model out of scanned data. The comparison is based on the scanning and reconstruction of two relatively complex artistic sculptures and a number of\ ground truth" objects.
Unmanned Ground Vehicle Technology VI, 2004
In order to effectively navigate any environment, a robotic vehicle needs to understand the terrain and obstacles native to that environment. Knowledge of its own location and orientation, and knowledge of the region of operation, can greatly improve the robot's performance. To this end, we have developed a mobile system for the fast digitization of large-scale environments to develop the a priori information needed for prediction and optimization of the robot's performance. The system collects ground-level video and laser range information, fusing them together to develop accurate 3D models of the target environment. In addition, the system carries a differential Global Positioning System (GPS) as well as an Inertial Navigation System (INS) for determining the position and orientation of the various scanners as they acquire data. Issues involved in the fusion of these various data modalities include: Integration of the position and orientation (pose) sensors' data at varying sampling rates and availability; Selection of "best" geometry in overlapping data cases; Efficient representation of large 3D datasets for real-time processing techniques. Once the models have been created, this data can be used to provide a priori information about negative obstacles, obstructed fields of view, navigation constraints, and focused feature detection.