Investigation of systematic errors for the hybrid and panoramic scanners

The existence of terrestrial laser scanners (TLSs) with capability to provide dense three-dimensional (3D) data in short period of time has made it widely used for the many purposes such as documentation, management and analysis. However, similar to other sensors, data obtained from TLSs also can be impaired by errors coming from different sources. Then, calibration routine is crucial for the TLSs to ensure the quality of the data. Through self-calibration, this study has performed system calibration for hybrid (Leica ScanStation C10) and panoramic (Faro Photon 120) scanner at the laboratory with dimensions 15.5m x 9m x 3m and more than hundred planar targets that were fairly distributed. Four most significant parameters are derived from well-known error sources of geodetic instruments as constant (a0), collimation axis (b0), trunnion axis (b1) and vertical circle index (c0) errors. Data obtained from seven scan-stations were processed, and statistical analysis (e.g. t-test) has shown significant errors for the calibrated scanners

Terrestrial laser scanners pre-processing: registration and georeferencing

Terrestrial laser scanner (TLS) is a non-contact sensor, optics-based instrument that collects three dimensional (3D) data of a defined region of an object surface automatically and in a systematic pattern with a high data collecting rate. This capability has made TLS widely applied for numerous 3D applications. With the ability to provide dense 3D data, TLS has improved the processing phase in constructing complete 3D model, which is much simpler and faster. Pre-processing is one of the phases involved, which consisted of registration and georeferencing procedures. Due to the many error sources occur in TLS measurement, thus, pre-processing can be considered as very crucial phase to identify any existence of errors and outliers. Any presence of errors in this phase can decrease the quality of TLS final product. With intention to discuss about this issue, this study has performed two experiments, which involved with data collection for land slide monitoring and 3D topography. By implementing both direct and indirect pre-processing method, the outcomes have indicated that TLS is suitable for applications which require centimetre level of accuracy

A study about terrestrial laser scanning for reconstruction of precast concrete to support QCLASSIC assessment

Nowadays, terrestrial laser scanning shows the potential to improve construction productivity by measuring the objects changes using real-time applications. This paper presents the process of implementation of an efficient framework for precast concrete using terrestrial laser scanning that enables contractors to acquire accurate data and support Quality Assessment System in Construction (QLASSIC). Leica Scanstation C10, black/white target, Autodesk Revit and Cyclone software were used in this study. The results were compared with the dimensional of based model precast concrete given by the company as a reference with the AutoDesk Revit model from the terrestrial laser scanning data and conventional method (measuring tape). To support QLASSIC, the tolerance dimensions of cast in-situ & precast elements is +10 mm /-5 mm. The results showed that the root mean square error for a Revit model is 2.972 mm while using measuring tape is 13.687 mm. The accuracy showed that terrestrial laser scanning has an advantage in construction jobs to support QLASSIC

Investigation of datum constraints effect in terrestrial laser scanner self-calibration

The ability to provide rapid and dense three-dimensional (3D) data have made many 3D applications easier. However, similar to other optical and electronic instruments, data from TLS can also be impaired with errors. Self-calibration is a method available to investigate those errors in TLS observations which has been adopted from photogrammetry technique. Though, the network configuration applied by both TLS and photogrammetry techniques are quite different. Thus, further investigation is required to verify whether the photogrammetry principal regarding datum constraints selection is applicable to TLS self-calibration. To ensure that the assessment is thoroughly done, the datum constraints analyses were carried out using three variant network configurations: 1) minimum number of scan stations, 2) minimum number of surfaces for targets distribution, and 3) minimum number of point targets. Via graphical and statistical, the analyses of datum constraints selection have indicated that the parameter correlations obtained are significantly similar

Terrestrial laser scanners datum transformation: insignificant analysis of scale factor

Due to the measurement mechanism employed by terrestrial laser scanners (TLSs), the pre-processing procedure has become crucial procedure to orient all acquired data into global or ground coordinate system. Rather than utilising all seven-transformation parameters, most of TLS practitioners have neglected the scale factor. Taking into consideration the uncertainties in deriving range data, disregarding the scale factor in datum transformation computation could jeopardise the quality of pre-processed results. To rigorously examine this argument, two experiments have been designed by considering the element of multi distances and multi sensors. Utilising phase (i.e. Faro Focus 3D) and pulse-based (i.e. Leica ScanStation C10) scanners, both experiments were carried out with computation of seven (7) transformation parameters and scale factors were extracted for the assessment. With the aid of statistical analysis, the computed scale factors were mathematically differentiate to the ideal value (i.e. 1.000 or no scale effect). Under 95% confidence level, the null hypotheses for both experiments have indicate an agreement that scale factor can be neglected in datum transformation process for both types of terrestrial laser scanners

Improvement in accuracy for three-dimensional sensor (Faro Photon 120 scanner)

The ability to provide actual information and attractive presentation, three-dimensional (3D) information has been widely used for many purposes especially for documentation, management and analysis. As a non-contact 3D sensor, terrestrial laser scanners (TLSs) have the capability to provide dense of 3D data (point clouds) with speed and accuracy. However, similar to other optical and electronic sensors, data obtained from TLSs can be impaired by errors coming from different sources. In order to ensure the high quality of the data, a calibration routine is crucial for TLSs to make it suitable for accurate 3D applications (e.g. industrial measurement, reverse engineering and monitoring). There are two calibration approaches available: 1) component, and 2)system calibration. Due to the requirement of special laboratories and tools to perform component calibration, the task cannot be carried out by most TLSs users. In contrast, system calibration only requires a room with appropriate targets. Through self-calibration, this study involved a system calibration for Faro Photon 120 scanner in a laboratory with dimensions of 15.5m x 9m x 3m and 138 well-distributed planar targets. Four calibration parameters were derived from well-known error sources of geodetic instruments. Data obtained using seven scan stations were processed, and statistical analysis (e.g. t-test) shows that all error models, the constant error (8.9mm), the collimation axis error (-4.3), the trunnion axis error (-11.6) and the vertical circle index error (8.0) were significant for the calibrated 3D sensor

Improvement in accuracy for threedimensional sensor (Faro Photon 120 Scanner)

The ability to provide actual information and attractive presentation, three-dimensional (3D) information has been widely used for many purposes especially for documentation, management and analysis. As a non-contact 3D sensor, terrestrial laser scanners (TLSs) have the capability to provide dense of 3D data (point clouds) with speed and accuracy. However, similar to other optical and electronic sensors, data obtained from TLSs can be impaired by errors coming from different sources. In order to ensure the high quality of the data, a calibration routine is crucial for TLSs to make it suitable for accurate 3D applications (e.g. industrial measurement, reverse engineering and monitoring). There are two calibration approaches available: 1) component, and 2) system calibration. Due to the requirement of special laboratories and tools to perform component calibration, the task cannot be carried out by most TLSs users. In contrast, system calibration only requires a room with appropriate targets. Through self-calibration, this study involved a system calibration for Faro Photon 120 scanner in a laboratory with dimensions of 15.5m x 9m x 3m and 138 well-distributed planar targets. Four calibration parameters were derived from well-known error sources of geodetic instruments. Data obtained using seven scan stations were processed, and statistical analysis (e.g. t-test) shows that all error models, the constant error (8.9mm), the collimation axis error (-4.3”), the trunnion axis error (-11.6”) and the vertical circle index error (8.0”) were significant for the calibrated 3D sensor

Investigation of systematic errors for the hybrid and panoramic scanners

The existence of terrestrial laser scanners (TLSs) with capability to provide dense three-dimensional (3D) data in short period of time has made it widely used for the many purposes such as documentation, management and analysis. However, similar to other sensors, data obtained from TLSs also can be impaired by errors coming from different sources. Then, calibration routine is crucial for the TLSs to ensure the quality of the data. Through self-calibration, this study has performed system calibration for hybrid (Leica ScanStation C10) and panoramic (Faro Photon 120) scanner at the laboratory with dimensions 15.5m x 9m x 3m and more than hundred planar targets that were fairly distributed. Four most significant parameters are derived from well-known error sources of geodetic instruments as constant (a0), collimation axis (b0), trunnion axis (b1) and vertical circle index (c0) errors. Data obtained from seven scan-stations were processed, and statistical analysis (e.g. t-test) has shown significant errors for the calibrated scanner

Adaption of invariant features in image for point clouds registration

Currently, coarse registration methods for scanner are required heavy operator intervention either before or after scanning process. There also have an automatic registration method but only applicable to a limited class of objects (e.g. straight lines and flat surfaces). This study is devoted to a search of a computationally feasible automatic coarse registration method with a broad range of applicability. Nowadays, most laser scanner systems are supplied with a camera, such that the scanned data can also be photographed. The proposed approach will exploit the invariant features detected from image to associate point cloud registration. Three types of detectors are included: scale invariant feature transform (SIFT), 2) Harris affine, and 3) maximally stable extremal regions (MSER). All detected features will transform into the laser scanner coordinate system, and their performance is measured based on the number of corresponding points. Several objects with different observation techniques were performed to evaluate the capability of proposed approach and also to evaluate the performance of selected detectors

Terrestrial laser scanners self-calibration study: datum constraints analyses for network configurations

Similar to other electronic instruments, terrestrial laser scanner (TLS) can also inherent with various systematic errors coming from different sources. Self-calibration technique is a method available to investigate these errors for TLS which were adopted from photogrammetry technique. According to the photogrammetry principle, the selection of datum constraints can cause different types of parameter correlations. However, the network configuration applied by TLS and photogrammetry calibrations are quite different, thus, this study has investigated the significant of photogrammetry datum constraints principle in TLS self-calibration. To ensure that the assessment is thorough, the datum constraints analyses were carried out using three variant network configurations: 1) minimum number of scan stations; 2) minimum number of surfaces for targets distribution; and 3) minimum number of point targets. Based on graphical and statistical, the analyses of datum constraints selection indicated that the parameter correlations obtained are significantly similar. In addition, the analysis has demonstrated that network configuration is a very crucial factor to reduce the correlation between the calculated parameters