Coordinate Conversion Research Articles

Tectonic fractures induced by strike-slip faulting in intracratonic ultradeep carbonate rocks: Insights from the finite element method and self-adaptive constraints computational model for boundary conditions

Numerical simulations of the paleostress field during a period of tectonic fracture formation and rock failure criteria are used to quantitatively predict the development and occurrence of tectonic fractures induced by the formation of the SB18 fault zone in the Middle Ordovician Yijianfang Formation of the Shunnan area, Tarim Basin, China. The results of acoustic emission experiments, mechanical property measurements, and tectonic fracture occurrence observations obtained from core descriptions and fullbore formation microimager logs are combined with the Andersonian model of faulting and the finite element method, which is widely used for the numerical simulation of stress fields, to investigate the paleotectonic and in situ stress fields via numerical simulation. The quantitative prediction of the opening pressure and opening sequence of tectonic fractures is based on the occurrence of tectonic fracture, numerical simulation of in situ stresses, and coordinate system conversion. The results show that the width of the fracture zone induced by strike-slip faulting is ∼310 m. The degree of fracture development is significantly increased when the Young’s modulus, paleostress difference, and paleostress difference coefficient of the rock are elevated. The current horizontal principal stress is positively correlated with the distance from the fault, and the elevated areal density of the secondary faults causes a clockwise deflection of the horizontal stress direction. SSE-striking shear fractures with orientations ranging from 140° to 150° and two sets of tensional fractures with orientations ranging from −40° to −35° and 55° to 60° are preferentially opened in the water injection development stage of the reservoir. As the horizontal stress difference, horizontal stress difference coefficient, and angle between the maximum horizontal principal stress and a fracture decrease, the fracture opening pressure decreases. At the structural highs (burial depths <6225 m) and lows (burial depths >6225 m), the fracture burial depth is positively and negatively correlated with the opening pressure, respectively. Quantitative prediction of tectonic fracture developmental characteristics, opening pressure, and the opening sequence and investigation of the main factors that control their development can help to identify and support opportunities for hydrocarbon exploration and development of fractured carbonate reservoirs.

A method for estimating ship berthing angle based on 2D bird's eye view point cloud

The accurate estimation of berthing angle is essential for the parallel berthing of inshore ships. Herein, a new method for calculating the ship berthing angle using a shore-based LiDAR system is proposed. First, the LiDAR-scanned point cloud data is preprocessed, including coordinate conversion, noise filtering, and data downsampling. Then, the processed point cloud data is projected onto a two-dimensional (2D) plane, and the height value is used as the pixel value to generate bird's eye view (BEV) images. Finally, an improved Hough transform is proposed to detect the straight line representing the ship's nearshore profile in the BEV images and replace the ship midline with the detected line for calculating the berthing angle. The performance of the proposed method is verified by applying it on simulated and real ship data. Simulation experiment results show that the maximum absolute error of our method is only 0.151°. Real ship experiments were conducted at Dalian Port (China) to verify the reliability and stability of the method compared with other berthing angle estimation methods and the compass equipment. Overall, the proposed method can effectively obtain the berthing angle of ships, assist in parallel berthing, and improve berthing efficiency.

SPATIAL AND TEMPORAL DISTRIBUTION OF LISTINGS ON AIRBNB AND BOOKING.COM AS SHARING ECONOMY PLATFORMS IN THE TOURISM DESTINATION OF MARAMURES LAND ROMANIA

The innovations brought by the sharing economy model through digital booking platforms have produced changes in the dynamic of the accommodation supply in many tourism destinations. The fastness with which changes occur has left this market segment either largely unaccounted for statistically, or poorly regulated, and Maramureș Land, a known cultural and rural tourism destination with inherent regional and local particularities, is no exception. The study raises the issue of evidence regarding the level of adoption and the true scale of the accommodation supply in the area by focusing on listings from two of the most popular digital booking platforms – Booking.com and Airbnb, an aspect that can support policy-making adapted to its specific characteristics. These objectives were pursued through an empirical methodological approach to map the spatiotemporal distribution of listings from the area of Maramureș Land between 2010 and 2023. The methodology assumed the creation of an M.Excel database with all listings from the area, the extraction of descriptive variables and coordinates, the conversion of coordinates into vector point data, and the subsequent analysis using vector and attribute data processing instruments in QGIS.

Electroosmotic and Gyrotactic Microorganisms Effects on MHD Al2O3-Cu/Blood Hybrid Nanofluid Flow through Multi-Stenosed Bifurcated Artery.

The purpose of this study is to investigate the electroosmotic flow of a hybrid nanofluid (Al2O3-Cu/Blood) with gyrotactic microorganisms through a bifurcated artery with mild stenosis in both parent and daughter arteries. The flow is subjected to a uniform magnetic field, viscous dissipation, and a heat source. The governing equations undergo the non-dimensional transformation and coordinate conversion to regularize irregular boundaries, then solve the resulting system using the Crank-Nicolson method. In both sections of the bifurcated artery (parent and daughter artery), the wall shear stress (WSS) profile decreases with increasing stenotic depth. Nusselt profile increases with an increase in the heat source parameter. The present endeavour can be beneficial for designing better biomedical devices and gaining insight into the hemodynamic flow for therapeutic applications in the biomedical sciences.

Aircraft engine danger areas incursion detection using keypoint detection and IoT

Operational safety at airports has long been a subject of active research, with a growing focus on the safety of aircraft stands in recent years. The phase during which an aircraft taxi into its designated stand with engines still running poses safety risks to surrounding vehicles. However, there is currently a lack of effective methods for detecting potential conflicts and hazards during this taxiing phase. To address this issue, this study utilizes apron activity videos as a monitoring data source and introduces an integrated Internet of Things (IoT) conflict detection model. This system combines object detection, engine keypoint detection, coordinate conversion, and conflict warning system to provide timely alerts when vehicles incursion into the engine danger areas. Firstly, the paper streamlines the fourth-level branch and network of HRNet, resulting in the HRNet-3stage network. This network is then compared with Lite-HRNet to determine the optimal choice. Secondly, Recognizing the limitations of traditional video conflict detection based on pixel distance, a fixed monitoring camera coordinate conversion algorithm is designed to convert pixel coordinates into actual coordinates on the aircraft stand, thereby improving the accuracy of conflict detection based on distance measurement. Thirdly, considering the risks associated with engine inlet and exhaust, engine design parameters, static spacing standards, and the dynamic anti-collision process within the aircraft stand, the study proposes a method for classifying four types of aircraft engine danger areas. Corresponding conflict detection models are designed for potential scraping incidents when vehicles incursion into these danger areas. Upon detecting a vehicle entering the aircraft engine danger areas, the IoT system sends warning messages through the airport control tower monitoring system. Finally, we construct an apron sandbox to validate the conflict detection model. This validation results in an impressive F1-score exceeding 90% and a detection delay of less than 100 ms. Our innovative approach, supported by keypoint detection networks and IoT, effectively addresses the detection of critical aircraft components within stands. It comprehensively analyzes incursion issues into engine danger areas, offering a novel perspective for understanding and mitigating potential conflicts arising from aircraft taxiing into stands.

An ontology‐based rule mapping approach for integrating IFC and CityGML

AbstractBuilding information modeling (BIM) and geographic information system (GIS) are often integrated to achieve more refined urban management. Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) are widely used standards in BIM and GIS. The main problem of the transformation of these two standards lies in the gap between them in geometry and semantics. This article introduces an ontology‐based rule mapping approach, achieving the transformation from IFC to CityGML through coordinate system conversion, geometric expression conversion, and semantic mapping. For semantic mapping, we have designed and established rules, enabling the effective mapping of the IFC model to the CityGML level of detail 0 (LOD0) to LOD4 model based on entities, appearance properties and building properties. To fully demonstrate the entire process, we give a detailed elaboration of the conversion of several IFC models.

A common points selection method based on the uniformity of FLTMMS for pre-alignment of particle accelerators

High-precision pre-alignment of a magnet is a crucial step in the construction of a particle accelerator such as the Hefei Advanced Light Facility (HALF) or High Energy Photon Source (HEPS). To improve the accuracy and efficiency of pre-alignment, there are plans to build a four-station laser tracker multilateration measurement system (FLTMMS) at HALF. In the coordinate conversion and self-calibration processes of a FLTMMS, an unreasonable distribution of common points can lead to a loss of accuracy. A method for selecting common points based on uniformity in the FLTMMS is therefore proposed. In this method, the coordinate transformation space is divided according to the uniformity in different directions. The feasibility of our method is compared and analysed through coordinate conversion and self-calibration experiments. Simulations show that with the same number of common points, this method leads to higher accuracy in coordinate conversion and self-calibration. The proposed method compensates for the loss of accuracy due to aggregation of common points. Comparative analyses show a clear positive relationship between the accuracy improvement effect and the difference in uniformity. The distribution of common points will change the accuracy distribution of FLTMMS. Our approach of providing essential references for pre-aligning HALF magnets has been applied to HEPS with extensive engineering experience, to verify the practicality of this method for engineering applications. In the actual measurements, self-calibration is performed using an edge measurement network, and coordinate conversion is conducted using angle measurements. Based on actual measurements, the self-calibration accuracy is 1.7 μm and a conversion accuracy is 14.8 μm. The results show that under the premise of satisfying precision, the method can reduce the number of common points, thus decreasing the cost of common points construction. Our study provides instructions for pre-alignment at HALF in the future.

A spatiotemporal distribution identification method of vehicle weights on bridges by integrating traffic video and toll station data

Real-time monitoring of the spatiotemporal distribution of vehicle weights on bridge decks is an important component of bridge structural health monitoring systems. However, it is still a challenge to identify the spatiotemporal distribution of vehicle weights on the whole bridge deck because the existing identification techniques are based on the theory of line of influence or need to install a weight-in-motion (WIM) system on the bridge. This paper proposes an information fusion-based identification method for the spatiotemporal distribution of vehicle weights without WIM installation, in which, (1) the traffic videos acquired by multiple cameras arranged along both sides of the bridge are used to detect the spatiotemporal distribution and license plate of the vehicles, and the weights obtained from the toll station are linked to the vehicles by matching the license plates. In addition, (2) a digital image correlation (DIC)-based vehicle tracking method is proposed to solve the problems of frame drop and missing detection and (3) a polynomial fitting-based coordinate transformation method is proposed to avoid the derivation of complicated coordinate conversion formula related to pinhole camera. The efficiency and accuracy of the proposed identification approach are verified by the field data collected from a cable-stayed bridge and nearby toll stations. The results indicate that our proposed method is a feasible and reliable solution for identifying spatiotemporal distribution of vehicle weights on bridges.

Dynamic modeling of spur gear system considering the coupling effect between bearing deflection and gear mesh stiffness

Bearing deflection has a direct impact on the mesh condition of gear systems via the center distance of the gear pair and corner contact. These factors need to be considered to accurately model the time-varying mesh stiffness and dynamic responses of gears. To address this issue, a spatial coordinate conversion is used to obtain the instantaneous spatial position of the gear pair under the bearing deflection. The tooth pair separation distance is derived through the geometric relationship analysis to model the corner contact effect. A dynamic model is established which employs a step-to-step time integration algorithm that considers the coupling effect between bearing deflection and time-varying mesh stiffness to obtain the dynamic response of the spur gear system. The simulation results of the proposed model show good agreement with the experimental results which demonstrate that the proposed model enables a proper analysis of the influence of bearing deflection on gear mesh behavior. This study provides an original dynamic model for analyzing the dynamic performance of the gear system considering the influence of bearing deflection.

System for Tracking Aircraft Ground Movement Utilizing Artificial Intelligence

Using a virtual ATC tower is one aspect of the airport digitization initiative, which aims to cut costs. Technology for tracking and detecting aircraft is required to guarantee the security of the deployment of virtual ATC towers. The invention of visual artificial intelligence that can recognize and follow aircraft ground movement in an airport is presented in this study. One feature that should be developed in this study is the capacity to issue a warning if two aircraft are in close proximity to one another. The techniques consist of a coordinate system conversion from pixels to meters for aircraft separation computation, the Deep SORT object tracking algorithm, and the YOLOv4 object recognition algorithm that has been trained using Image Dehazing Filter. Next, a fair-condition recorded airport video is used to validate the model. With a mean average precision score of 95.92%, the trained YOLOv4 model was able to track every aircraft in the video, and with an error of 5.09%, the aircraft separation warning system functioned as expected. An airport’s possible use of an aircraft ground movement tracker was demonstrated by the constructed model.

Research on the Innovation of Education Mode of Art and Design Specialties in Colleges and Universities under the Background of Big Data

Abstract Art and design professional education can not keep up with the development speed of the industry, and there is no reference to the market demand data, failing to keep pace with the times, which brings many negative impacts on the employment of students. This paper suggests an art design professional education model that incorporates VR interactive scene technology for this reason. Through the double camera, we simulate the visual principle of the human eye, collect three-dimensional data from VR interactive scenes, and use the image coordinate system and pixel coordinate system conversion operations to pre-process the collected data. The optimal layout solution is sought by adjusting the layout to generate a realistic 3D model of the teaching scene and to realize the construction of the VR interactive scene. The principle and implementation process of the art professional education model supported by the VR interactive scene is elaborated, and the experimental comparison method is used to empirically analyze the art and design professional education model integrating VR technology. The results show that there is a significant difference between the experimental group and the control group in the dimensions of adaptability (0.004) and uniqueness (0.044) of design thinking and the cultivation of design thinking ability (0.016) (P<0.05), which indicates that the art and design professional education model integrating the VR scene interaction technology constructed in this paper has a significant effect on the enhancement of design thinking ability of college students.

Low-loss integrated dynamic polarization controller based on silicon photonics

<sec>A dynamic polarization controller (DPC) is an important component in fiber optic communication, optical imaging, and quantum technologies. The DPC can transform any input state of polarization (SOP) into any desired SOP to overcome polarization-related impairments resulting from high internally and externally induced birefringence. In this work, a low-loss silicon photonics-integrated DPC is designed and demonstrated experimentally. The whole chip is fabricated by using industry-standard silicon-on-insulator technology. Using the edge-coupling method, the coupler loss is reduced to less than 2 dB, and the total loss of DPC is reduced to 5.7 dB. Using a variable-step simulated annealing method, for a low-noise photodetector and high-static-extinction-ratio device, a dynamic polarization extinction ratio can reach more than 30 dB. The size of the DPC on the chip is 5.20 mm × 0.12 mm × 0.80 mm.</sec><sec>The DPC utilizes a 0°/45°/0°/45° structure, which can realize arbitrary polarization-based coordinate conversion with endless polarization control. The 0° and 45° transform structures and matrices are presented, and the principle of the 0° and 45° structures is explained in detail by using the Poincaré sphere.</sec><sec>A simulation using Lumerical is conducted to optimize the polarization rotator-splitter, which can transform the TM<sub>0</sub> mode light in one waveguide into the TE<sub>0</sub> mode light in the other waveguide while the TE<sub>0</sub> mode light in one waveguide remains unchanged. Based on the optimized structure, the static polarization extinction ratio of DPC can be measured to be a value greater than 40 dB.</sec><sec>The thermal phase shift (TPS) is characterized by using a Mach–Zehnder modulator. The length of the TPS is 400 μm, and the resistance of the metal heater is 2.00 kΩ. The maximum power consumed by the four TPSs is a total of 0.2 W. The modulation bandwidth of the DPC designed by our group is approximately 30 kHz. By considering an applied voltage of 5.6 V in the case of the TPS, the bandwidth–voltage product is 5.6 × 30 = 168 kHz·V.</sec><sec>To optimize the DPC parameters, such as the step length, electronic noise, and static polarization extinction ratio, numerical simulation results of the simulated annealing approach are analyzed in detail.</sec><sec>In conclusion, a low-loss silicon photonics-integrated DPC is designed and demonstrated experimentally. A dynamic polarization extinction ratio is obtained to be greater than 30 dB by using the variable-step simulated annealing method. The DPC is expected to be utilized in fiber or quantum communication systems to minimize size and further decrease costs.</sec>

Low-loss integrated dynamic polarization controller based on silicon photonics

<sec>A dynamic polarization controller (DPC) is an important component in fiber optic communication, optical imaging, and quantum technologies. The DPC can transform any input state of polarization (SOP) into any desired SOP to overcome polarization-related impairments resulting from high internally and externally induced birefringence. In this work, a low-loss silicon photonics-integrated DPC is designed and demonstrated experimentally. The whole chip is fabricated by using industry-standard silicon-on-insulator technology. Using the butting coupling method, the coupler loss is reduced to less than 2 dB, and the total loss of DPC is reduced to 5.7 dB. Using a variable-step simulated annealing method, for a low-noise photodetector and high-static-extinction-ratio device, a dynamic polarization extinction ratio can reach more than 30 dB. The size of the DPC on the chip is 5.20 mm × 0.12 mm × 0.80 mm.</sec><sec>The DPC utilizes a 0°/45°/0°/45° structure, which can realize arbitrary polarization-based coordinate conversion with endless polarization control. The 0° and 45° transform structures and matrices are presented, and the principle of the 0° and 45° structures is explained in detail by using the Poincaré sphere.</sec><sec>A simulation using Lumerical is conducted to optimize the polarization rotator-splitter, which can transform the TM<sub>0</sub> mode light in one waveguide into the TE<sub>0</sub> mode light in the other waveguide while the TE<sub>0</sub> mode light in one waveguide remains unchanged. Based on the optimized structure, the static polarization extinction ratio of DPC can be measured to be a value greater than 40 dB.</sec><sec>The thermal phase shift (TPS) is characterized by using a Mach–Zehnder modulator. The length of the TPS is 400 μm, and the resistance of the metal heater is 2.00 kΩ. The maximum power consumed by the four TPSs is a total of 0.2 W. The modulation bandwidth of the DPC designed by our group is approximately 30 kHz. By considering an applied voltage of 5.6 V in the case of the TPS, the bandwidth–voltage product is 5.6 × 30 = 168 kHz·V.</sec><sec>To optimize the DPC parameters, such as the step length, electronic noise, and static polarization extinction ratio, numerical simulation results of the simulated annealing approach are analyzed in detail.</sec><sec>In conclusion, a low-loss silicon photonics-integrated DPC is designed and demonstrated experimentally. A dynamic polarization extinction ratio is obtained to be greater than 30 dB by using the variable-step simulated annealing method. The DPC is expected to be utilized in fiber or quantum communication systems to minimize size and further decrease costs.</sec>

Identification and localization of transmission lines for live working in distribution network

In this paper, aiming at the current distribution network with power operation in the presence of outdoor bright light, the operating scene is complex and not fixed, the transmission lines and lead samples are small and uneven, leading to poor accuracy of machine learning and other methods of distribution network with power operation robot identification and localization, this paper selects three-dimensional LIDAR to design a set of support vector machine (SVM) classifier and correlation analysis based on the target recognition method. This paper selects three-dimensional LIDAR to design a set of support vector machine (SVM) classifier and correlation analysis based on the target recognition method. First, in the context of power distribution network operations, we have explored various filtering methods suitable for preprocessing transmission line data. These methods aim to remove outliers and clutter from point clouds, thus enhancing both point cloud quality and processing speed. This, in turn, improves the efficiency of real-time on-site detection. We conducted experimental comparisons of various clustering algorithms and opted for a region-based point cloud clustering algorithm to achieve the segmentation of individual point clouds. Secondly, we proposed a multi-feature composite approach based on the Viewpoint Feature Histogram (VFH) features, which helps maintain the scale-invariant characteristics of the features. We then introduced a multi-feature composite criterion based on VFH features to extract features from segmented point clouds. Subsequently, an SVM classifier based on this composite feature criterion was developed to achieve target identification and classification. Experimental results have demonstrated improved accuracy in target identification. Finally, we integrated this system with a bucket-arm vehicle for coordinate conversion and precise navigation of the robot to the target station. This method significantly improves the overall operational efficiency of power distribution tasks.

Next-generation sequencing analysis with a population-specific human reference genome.

Next-generation sequencing (NGS) has become widely available and is routinely used in basic research and clinical practice. The reference genome sequence is an essential resource for NGS analysis, and several population-specific reference genomes have recently been constructed to provide a choice to deal with the vast genetic diversity of human samples. However, resources supporting population-specific references are insufficient, and it is burdensome to perform analysis using these reference genomes. Here, we constructed a set of resources to support NGS analysis using the Japanese reference genome, JG. We created resources for variant calling, variant-effect prediction, gene and repeat element annotations, read mappability, and RNA-seq analysis. We also provide a resource for reference coordinate conversion for further annotation enrichment. We then provide a variant calling protocol with JG. Our resources provide a guide to prepare sufficient resources for the use of population-specific reference genomes and can facilitate the migration of reference genomes.

Using VoteNet to detect beverage bottles

When using point cloud to detect indoor objects, the collected point cloud often has a lot of noise, such as points that are too far away, background points that have nothing to do with the objects to be detected, which will have a bad impact on the detection. In order to solve these problems, a method is proposed to preprocess the collected original point cloud before training and prediction. First, the points that are too far away should be eliminated. Second, the background such as the table should be eliminated as much as possible. Then, the coordinate conversion is required for the point cloud. Finally, VoteNet is used to train these processed point clouds to obtain the model, which is then used for prediction. The experimental results show that the model is good when using these processed point cloud data for training and prediction. In addition, this paper proposes to obtain point cloud by scanning objects, and then process the obtained point cloud to expand the dataset. The significance of this study is using the collected point cloud data for final training and prediction and expanding the dataset without using 3D cameras.

Research on the Relative Position Detection Method between Orchard Robots and Fruit Tree Rows.

The relative position of the orchard robot to the rows of fruit trees is an important parameter for achieving autonomous navigation. The current methods for estimating the position parameters between rows of orchard robots obtain low parameter accuracy. To address this problem, this paper proposes a machine vision-based method for detecting the relative position of orchard robots and fruit tree rows. First, the fruit tree trunk is identified based on the improved YOLOv4 model; second, the camera coordinates of the tree trunk are calculated using the principle of binocular camera triangulation, and the ground projection coordinates of the tree trunk are obtained through coordinate conversion; finally, the midpoints of the projection coordinates of different sides are combined, the navigation path is obtained by linear fitting with the least squares method, and the position parameters of the orchard robot are obtained through calculation. The experimental results show that the average accuracy and average recall rate of the improved YOLOv4 model for fruit tree trunk detection are 5.92% and 7.91% higher, respectively, than those of the original YOLOv4 model. The average errors of heading angle and lateral deviation estimates obtained based on the method in this paper are 0.57° and 0.02 m. The method can accurately calculate heading angle and lateral deviation values at different positions between rows and provide a reference for the autonomous visual navigation of orchard robots.

Research on the design of booth space in furniture exhibitions based on big data analysis

Abstract In this paper, we first use VR technology to spatially calibrate the flat images of furniture booths and use a fisheye camera to obtain the visual features of booth space layout with coordinate information and color information in 3D space to construct a 3D geometric model. Then, the booth layout framework is used to extract the scene information, and the visualization processing and fusion of layout nodes are realized using coordinate conversion to complete the multi-user interactive genetic algorithm-based booth space layout to visualize and analyze the furniture layout of the booth space. After testing, we found that before optimizing, the area occupied by individual furniture SA tends to increase with the increase in a number of furniture. After optimization, the average area utilization of the booth increased by 23.6%, the number of furniture that can be accommodated in a single furniture area increased by 81.82% on average, and the booth space utilization was highly improved.

Exact and heuristic formulae to compute the geodetic height from the ellipse equation

The conversion of the cartesian coordinates of a point to its geodetic equivalent coordinates in reference to the geodetic ellipsoid is one of the main challenges in geodesy. The ellipse equation in the meridian plane significantly influences the value of the geodetic coordinates. This research analyzes this influence and how it can contribute to their solutions. The study investigates the mathematical relation between them and presents an exact formula relating to the geodetic height and the ellipse equation. In addition, a heuristic formula for the relation between the geodetic height and the ellipse equation is proposed, which is independent of the geodetic latitude and has a relative accuracy better than 99.9 %. The calculation is stable, and the cost is low.

Precise plane registration with multiple geometric feature matching and weighted least squares estimation

Point cloud registration is a fundamental problem for 3D laser scanning technology, which is extensively applied in geographic entity modelling such as 3D reconstruction of urban roads and buildings. Registration accuracy is one of the main focuses for these applications. However, noisy points, limited overlap, varying data sources, and differing measuring accuracy may cause changes between point cloud sets and reduce registration accuracy. This paper introduces an automatic plane registration method for urban roads and building scenes, which does not need manual on-site deployment. Firstly, plane primitives are extracted using voxel-based filtering region growth. Next, corresponding planes for the extracted primitives are identified by leveraging saliency features and constructing adjacency matrices. Finally, plane registration is achieved using a weighted plane coordinate conversion model. Through real-world scene experimentation, an overall accuracy of 10 cm and a segmental registration accuracy of 5–6 cm is achieved with our method, outperforming both feature point-based and global point cloud registration approaches in terms of efficiency and accuracy.