Empirical Development of 3D Terrain Processing Platform for Autonomous Excavation System

Similar documents
3D Grid Size Optimization of Automatic Space Analysis for Plant Facility Using Point Cloud Data

포인트클라우드파일의측점재배치를통한파일참조옥트리의성능향상

PAD Based 3D Earthwork BIM Design Module for Machine Guidance

VIRTUAL GRAPHIC REPRESENTATION OF CONSTRUCTION EQUIPMENT FOR DEVELOPING A 3D EARTHWORK BIM

Applicability Estimation of Mobile Mapping. System for Road Management

Application of isight for Optimal Tip Design of Complex Tool Holder Spindle

A light weight algorithm for large-scale BIM data for visualization on a web-based GIS platform

RAPID 3D OBJECT RECOGNITION FOR AUTOMATIC PROJECT PROGRESS MONITORING USING A STEREO VISION SYSTEM

MERGING POINT CLOUDS FROM HETEROGENEOUS 3D SCANNERS FOR FAST UPDATE OF AN EARTHWORK SITE MODEL

Integrating the Generations, FIG Working Week 2008,Stockholm, Sweden June 2008

Determination of the Parameter for Transformation of Local Geodetic System to the World Geodetic System using GNSS

ctbuh.org/papers Structural Member Monitoring of High-Rise Buildings Using a 2D Laser Scanner Title:

Slope Stability of Open Pit Mine in 2D & 3D

A Study on Development of Azimuth Angle Tracking Algorithm for Tracking-type Floating Photovoltaic System

Displacement Conversion Algorithm and Performance Evaluation by Tunnel Tilt Meter Sensors 1

Investigation of Sampling and Interpolation Techniques for DEMs Derived from Different Data Sources

Geospatial Engineering Problems & Solutions Associated With NDP Roads, Tunnelling & Civil Engineering Projects Use of HDS Leica Laser Scanners

GTS NX INTERFACES AUTOCAD MIDAS GEN FOR TUNNEL SOIL PILE INTERACTION ANALYSIS

Automated Extraction of Buildings from Aerial LiDAR Point Cloud and Digital Imaging Datasets for 3D Cadastre - Preliminary Results

TLS DEFORMATION MEASUREMENT USING LS3D SURFACE AND CURVE MATCHING

Explore Laser Scanning in As-Built Survey. Vijay Chowdhary SE: BIM/CIM

REAL-TIME OBJECT RECOGNITION AND MODELING FOR HEAVY-EQUIPMENT OPERATION

2D-based Indoor Mobile Laser Scanning for Construction Digital Mapping Application with BIM

TERRESTRIAL LASER SCANNING AND APPLICATION IN GEODETIC ENGINEERING

A Spatial Point Pattern Analysis to Recognize Fail Bit Patterns in Semiconductor Manufacturing

The Use of Photogrammetryin Measuring Geologic Structures and Creating a 3D Model on Exposed Rock Faces

3D Terrestrial Laser Scanner Innovative Applications for 3D Documentation

Polyhedral Building Model from Airborne Laser Scanning Data**

Critical Aspects when using Total Stations and Laser Scanners for Geotechnical Monitoring

Automatic registration of terrestrial laser scans for geological deformation monitoring

USE OF A POINT CLOUD CO-REGISTRATION ALGORITHM FOR DEFORMATION MEASURING

A 3D Scanner Based Technology for Land Levelling

AUTOMATIC EXTRACTION OF LARGE COMPLEX BUILDINGS USING LIDAR DATA AND DIGITAL MAPS

Stability Analysis of Slope Based on FLAC3D Using Strength Reduction Method. Speaker: Tran, Thi Kim Tu Advisor: Chuen Fa Ni Date: 2017/03/02

Optimal design of floating platform and substructure for a spar type wind turbine system

INFORMATION-ORIENTED DESIGN MANAGEMENT SYSTEM PROTOTYPE

Ability of Terrestrial Laser Scanner Trimble TX5 in Cracks Monitoring at Different Ambient Conditions

APPLICATION OF 3D TERRESTRIAL LASER SCANNING IN THE PROCESS OF UPDATE OR CORRECTION OF ERRORS IN THE CADASTRAL MAP

DEVELOPMENT OF CROSS SECTION MANAGEMENT SYSTEM IN TUNNEL USING TERRESTRIAL LASER SCANNING TECHNIQUE

TERRESTRIAL LASER SCANNER TECHNIC AS A METHOD FOR IDENTIFICATION AREAS OF SLOPS

Automatic Pipeline Generation by the Sequential Segmentation and Skelton Construction of Point Cloud

3D Terrain Modelling of the Amyntaio Ptolemais Basin

X-PAD Ultimate. The Ultimate solution in the field. Works when you do

Laser Scanning. 3D Model is not existing and is required for: studies revamping maintenance HSE integration in another 3D model archiving

Interdisciplinary Approach to Design, Analysis, and Modeling of Deformation Surveys

ASSETS DATA INVENTORY BASED ON BUILDING INFORMATION MODELLING

GLOBAL EXPERIENCE LOCAL KNOWLEDGE

BIM for infrastructure make easy with Laser Scanner. 17 October Beng Chieh Quah Head of Marketing Asia Pacific

Comparison of point clouds captured with terrestrial laser scanners with different technical characteristic

Experiments on Generation of 3D Virtual Geographic Environment Based on Laser Scanning Technique

Terrain Modeling and Mapping for Telecom Network Installation Using Scanning Technology. Maziana Muhamad

Trimble MX2 mobile mapping

Surveying like never before

AN ITERATIVE ALGORITHM FOR MATCHING TWO ROAD NETWORK DATA SETS INTRODUCTION

Computer Rubbings with Three-Dimensional Measurement Data

VISUALIZATION OF GEOINFORMATION IN DAM DEFORMATION MONITORING

International Journal of Civil Engineering and Geo-Environment. Close-Range Photogrammetry For Landslide Monitoring

1 Introduction. Myung Sik Kim 1, Won Jee Chung 1, Jun Ho Jang 1, Chang Doo Jung 1 1 School of Mechatronics, Changwon National University, South Korea

A new geodetic methodology for the accurate Documentation and Monitoring of inaccessible surfaces.

Rectification of distorted elemental image array using four markers in three-dimensional integral imaging

Modelling of Tunnels in 2D & 3D

3GSM GmbH. Plüddemanngasse 77 A-8010 Graz, Austria Tel Fax:

RECOMMENDATION ITU-R P DIGITAL TOPOGRAPHIC DATABASES FOR PROPAGATION STUDIES. (Question ITU-R 202/3)

Design and Implementation of Tunnel Displacement Management System Based on Sensor Networks 1

Virtually Real: Terrestrial Laser Scanning

Application of Dijkstra s Algorithm in the Smart Exit Sign

technical notes trimble realworks software

AUTOMATIC OBJECT RECOGNITION AND REGISTRATION OF DYNAMIC CONSTRUCTION EQUIPMENT FROM A 3D POINT CLOUD

CO-REGISTERING AND NORMALIZING STEREO-BASED ELEVATION DATA TO SUPPORT BUILDING DETECTION IN VHR IMAGES

Deformation Monitoring and Analysis of Structures Using Laser Scanners

Trimble Realworks Software

What can I model using RS 3?

Numerical simulation of 3-D seepage field in tailing pond and its practical application

NEW MONITORING TECHNIQUES ON THE DETERMINATION OF STRUCTURE DEFORMATIONS

A Novel Method for Activity Place Sensing Based on Behavior Pattern Mining Using Crowdsourcing Trajectory Data

TcpMDT. Digital Terrain Model Version 7.5. TcpMDT

Realworks Software. A Powerful 3D Laser Scanning Office Software Suite

Mobile 3D laser scanning technology application in the surveying of urban underground rail transit

DRAWING AND LANDSCAPE SIMULATION FOR JAPANESE GARDEN BY USING TERRESTRIAL LASER SCANNER

RealWorks Software. A Powerful 3D Laser Scanning Office Software Suite

[Youn *, 5(11): November 2018] ISSN DOI /zenodo Impact Factor

Automatic DTM Extraction from Dense Raw LIDAR Data in Urban Areas

Engineering and Environmental Geophysics with terratem

Attribute Assignment to Point Cloud Data and its usage

HIGH-DIMENSIONAL SPACE SEARCH SYSTEM FOR MULTI-TOWER CRANE MOTION PLANNING

AUTOMATIC MODELLING METHOD FOR STEEL STRUCTURES USING PHOTOGRAMMETRY

Improvement of Basic Functions for Visualizing Schedule and 3D Object in 4D CAD System

AUTOMATIC EXTRACTION OF ROAD MARKINGS FROM MOBILE LASER SCANNING DATA

3DCITY. Spatial Mapping and Holographic Tools for 3D Data Acquisition and Visualization of Underground Infrastructure Networks

AN ITERATIVE PROCESS FOR MATCHING NETWORK DATA SETS WITH DIFFERENT LEVEL OF DETAIL

2011 Bentley Systems, Incorporated. Bentley Descartes V8i Advancing Information Modeling For Intelligent Infrastructure

2D & 3D Semi Coupled Analysis Seepage-Stress-Slope

Minimizing Thin Glass Deflection in Flexible Display Manufacturing via Pin Map Optimization

QUALITY MONITORING OF LARGE STEEL BUILDINGS USING TERRESTRIAL LIDAR TECHNIQUE

The Existing Legal Cadastre in Israel Introduced in 1928 Based on Torrens principles (Registration of Title) Two-Dimensional Surface properties Owners

Design and Implementation a Virtualization Platform for Providing Smart Tourism Services

IDENTIFICATION DEFORMATION AREAS OF SLOPS USING TERRESTRIAL LASER

Rethinking Road Planning and Design Workflows:

EXTRACTION OF GEOMETRIC INFORMATION ON HIGHWAY USING TERRESTRIAL LASER SCANNING TECHNOLOGY

2011 Bentley Systems, Incorporated. Bentley Descartes V8i (SELECTseries 3) Advancing Information Modeling For Intelligent Infrastructure

Transcription:

Empirical Development of 3D Terrain Processing Platform for Autonomous Excavation System Seok Kim 1, Tae-yeong Kim 2, Soonwook Kwon 3, Jongwon Seo 4 1 Senior Researcher, Korean Institute of Civil Engineering and Building Technology, Goyang, South Korea (Corresponding Author: kimseok@kict.re.kr) 2 Researcher, Korean Institute of Civil Engineering and Building Technology, Goyang, South Korea 3 Professor, School of Civil, Architectural, and Environmental Engineering, SungKyunKwan University, Suwon, South Korea 4 Professor, Dept. of Civil and Environmental Engineering, Hanyang University, Seoul, South Korea ABSTRACT: With the advancement in measurement technology, the earthwork site can be scanned within a short period of time using 3D terrestrial laser scanning (TLS). While companies want to digitize an earthwork site for different purposes, they all ultimately want to achieve automated earthwork including earthwork planning and calculation of earthwork volume and operation of earthwork equipment. In this study, the 3D terrain processing platform was defined and developed as a prototype. The 3D terrain processing platform suggested in this study was developed as prototype software. It was also verified with simply scanned data and design drawings. In the verification of the DB using the 3D terrain processing platform, it was found that each analysis cell had the required information including coordinates, soil qualities, boring information, earthwork volume, work type (cutting or filling), etc. INTRODUCTION Earthwork is one of the essential construction works done to construct a building or a structure on the ground. Earthwork is a traditional work type, in which the work site is measured using a total station based on which an earthwork plan is provided. According to the plan, earthwork is executed to complete the entire work by using construction equipment such as bulldozer, backhoe loader, fork-crane, and truck. Since the mid-1990s, many studies have been conducted on intelligent excavation system to achieve automated earthwork. Here, an intelligent excavation system is a

technology to improve construction quality and productivity through the effective management of information technology and construction equipment [Singh, 1997]. In 2000, the initial form of an intelligent excavation system for automated earthwork was introduced as a construction machine equipped with a guidance system. In recent years, many studies have been conducted with the aim of developing a more advanced type of semi-automated or automated machine. The research findings of many studies on automated earthwork discuss how an earthwork site can be digitized, analyzed and utilized. As earthwork sites have too many uncertain factors to allow them to be digitized, many researchers have made efforts to solve this problem. Photogrammetry and the 3D terrestrial laser scanning system are the most notable methods. Rapid advancements are being made in these technologies, and many methodologies have been studied to digitize an earthwork site by using them. In particular, the 3D terrestrial scanning system is in wide use in many construction sites due to the accuracy of its measurements regardless of the source of light. For example, it is applied to many fields including calculation of earthwork [Du and Teng 2007, Slattery et al. 2012], deformation measurement of topography [Hashash et al. 2005, Hashash and Finno 2008, Prokop and Panholzer 2009], inspection of tunnel shape [Pejic 2013, Park et al. 2012, Nutterns et al. 2010], and deformation measurement of dam [Park et al. 2009]. It has also recently been used for 3D imaging of an earthwork site in order to provide fundamental data for automated control and guidance for heavy equipment such as fork-crane and bulldozer [Chae et al. 2009, Chae et al. 2011]. The purposes of digitizing an earthwork site can differ, but the ultimate purpose is to automate earthwork-related tasks such as establishing an earthwork plan, calculating the earthwork volume and operating earthwork equipment through the digitized earthwork site. Here, we should note that it is hard to consider an earthwork site as digitized even though the earthwork site has been scanned using a 3D scanner. As pointed out above, for the automation of earthwork, it should be possible to plan an earthwork plan, calculate earthwork volume and operate earthwork equipment; however, it is impossible to perform all of these functions with the scanned data alone. In this study we defined the 3D terrain processing platform required to realize automated earthwork based on the topographic function of the 3D terrestrial scanner, and developed it as a prototype. RESEARCH SCOPE AND METHODOLOGY The research scope and methodology for this study was set as described below to meet the following conditions and present a 3D terrain processing platform. 1 The interface function of the scanned data was not taken into account. If the earthwork site is scanned from a location, blind spots the laser scanner cannot capture cause distortion. For this reason, the data scanned from several locations are registered in order to increase the accuracy. However, the registering algorithm is not considered separately. Under the hypothesis that the scanned data is well registered, the data of point clouds are used.

2 The ground information is updated in consideration of the boring information and soil properties only. Information required for the earthwork may vary depending on the characteristics of the construction project or the construction area. However, only boring information and soil qualities commonly required for earthwork are considered in this study to update the ground property information. 3 The basic unit of this analysis is set as an analysis cell. To make it possible to make an earthwork plan, calculate earthwork volume and operate earthwork equipment, it is necessary to define the basic unit of information required for automated earthwork. The 3D scanned data cannot have volume itself because they are point clouds; therefore, they are not appropriate for an earthwork plan or the calculation of earthwork volume. Moreover, if they are entered for the entire space information after being converted into solid information, the practical analysis may take too much time because the data is too big. Therefore, an appropriate size of analysis cell is set as a basic unit to carry out a spatial analysis. IMPLEMENTATION OF 3D TERRAIN PROCESSING PLATFORM The 3D Terrain Processing Platform consists of 'updating soil properties, creating analysis cells and sending data to the integrated system. Of these, the updating soil properties and the creating analysis cells play the role of providing the analysis cells on which the basic properties are entered for the integrated system. Figure 1 illustrates how to process the data with the modules

FIG. 1. Process of the data in the integrated system 1. Loading of scanned data and plan drawing There are many noise points in the 3D point clouds collected from the 3D laser scanner at the site due to factors in the earthwork environment, such as trees and grass. Before soil properties are updated, the data is processed using a noise reduction function. Next, the plan drawing designed using software such as CAD is projected on the point cloud and then placed accurately by setting it with relative and absolute coordinates. FIG. 2. Loading of the scanned data & plan drawing

2. Updating Soil Properties Each point in the 3D point cloud has the information of X, Y, Z, RGB, and intensity. The module to update soil properties has the function of providing the geotechnical information needed to prepare an earthwork plan. The additional geotechnical information includes soil quality obtained through a boring investigation, state function, relative density, groundwater level, soil volume conversion factor, and weight of unit volume as calculated in the field density test, as shown in Table 1. Division Table 1. Additional geotechnical information Content Information from boring investigation Information from soil property test strata, altitude, groundwater level, relative density, state function Soil volume conversion factor (L, C), weight of unit volume 2.1 Update of the data from the boring investigation With respect to the data collected from the boring investigation, a user puts a serial number and the coordinates of each location on which the boring investigation was conducted. The boring investigation is usually done from the surface of the earth to the rock formation, which may be composed of many strata. For this reason, in this study, the strata were separated, and it was designed to enter the information such as altitude, stratum, density and dampness for each stratum. Once all the information was entered, it was interpolated in consideration of the earth s true surface to reflect the soil properties on all areas within the boundary as illustrated in Figure 3. FIG. 3. Boring investigation and soil properties information after the interpolation 2.2 Updating the data from the soil property test

On the other hand, the data obtained though the field density test was numbered and coordinates and altitude were then entered, and then the data from the field density test was entered for each location. Unlike the boring investigation, the soil density is tested in a test pit on the surface of the earth; for this reason, the depth from the surface was entered as appropriate for the test conditions, and then soil volume conversion factor (C,L) and weight of unit volume were input. Like the data from the boring investigation, it was also interpolated to reflect soil properties on the entire area within the boundary(figure 3). 3. Creating Analysis Cells The Creating Analysis Cells module sets the range of the boundary, and divides it into basic cell units. Next, the cell type is assigned and the data is entered. 3.1 Setting the range of the Cell The Cell analysis range was set in a cube in the center of the boundaries of the drawing projected on the point cloud. Here, the cube form is set for an index for Octree. Also, the unit length is set to the maximum distance in the X-, Y- and Z- directions in order to include all the boundaries, as shown in Equations 1 and Figure 4. Unit length of range = Max(X, Y, Z) (1) (a)x-, Y- directions FIG. 4. Cell range (b) Z- direction 3.2 Dividing a Cell Once the analysis range is set, it is divided into basic cell units; at this, the cells are systemically divided using the Octree algorithm. Octree is a conceptual extension from quadtree for 2D space, and it is the most efficient method for point cloud indexing. Octree algorithm is used to divide a cube-formed space (parent node) into eight identical sub-cubes (child node), each of which is assigned an identification number, and is also utilized in diverse studies related with 3D point cloud processing (Saxena et al., 1995; Marcchal, 2009). Octree repeatedly partitions a 3D space until the size of a cell comes to the most approximate size initially set by the user, and then an identification number is assigned to the cell(figure 5).

FIG. 5. Octree structure 3.3 Entering data on a Cell The cell information is entered on the central point of each cell with an identification number and expressed as shown in Figure 6. The cell information includes an identification number, soil properties, and earthwork. The earthwork is expressed as 00%C or 00%F, a combination of the ratio of soil in the cell with the work type. To be more specific, 00% describes what percentage of soil is in the cell and C is for cutting while F is for filling. In addition, the equipment location point is on the upper surface in the right direction of the point, and will be utilized in future planning for the earthwork in tandem with the central point of the cell.

FIG. 6. Cell data 4. Sending data to the integrated system The information of the cell is once composed and sent to Autonomous Excavation System to prepare an earthwork plan. At this time, the file can be saved and sent in a file format a user can open, such as *.dxf. The data sent is utilized as fundamental data both for path planning of the construction equipment and for fleet-type work planning. SUMMARY AND FUTURE RESEARCH As structures have become larger, the demand on the infrastructures has also increased, and with the gradual increase in demand for exploration of land humans hardly access, such as the polar regions, the deep sea and outer space, the demand for automated earthwork has also been on the rise. To help make automated earthwork a reality, we defined the analysis cell, a basic unit of the analysis of this study, and suggested how to utilize it. The 3D terrain processing platform largely consists of four parts. First, the basic work is carried out by loading the scanned data and the design drawing. Second, the updating soil properties module is presented to update the boring information and soil qualities required for the earthwork planning. Third, the analysis range is limited to set the basic unit of analysis, and then is divided into analysis cells and the creating analysis cell module to enter data on each cell is defined. Finally, the function of sending data to an integrated system is demonstrated. The 3D terrain processing platform is developed as a prototypical software in this study. It is verified with simple scanned data and the planned design. In the verification of the DB obtained through the 3D terrain processing platform, it was found that the required data was included in each cell, such as coordinates, soil qualities, boring information, earthwork volume, cutting or filling, etc. Cell types that reflected ground shape were not set in this study. The cell type should be included in the future to make a task planning for the heavy equipment or construction equipment.

ACKNOWLEDGMENTS This research was supported by a grant (14SCIP-B079344-01) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and Transport(MOLIT) of Korea government and Korea Agency for Infrastructure Technology Advancement(KAIA). REFERENCES Chae, M. J., Lee, G. W., Kim, J. R., Park, J. W., Yoo, H. S., Cho, M. Y., (2009) Development of the 3D Imaging System and Automatic Registration Algorithm for the Intelligent Excavation System (IES), Korea Journal of Construction Engineering and Management, 10(1), 136-145. Chae, M. J., Lee, G. W., Kim, J. Y., Park, J. W. and Cho, M. Y. (2011) A 3D surface modeling system for intelligent excavation system, Automation in Construction, Vol.20, No.7, 808-817. Du, J.C. and Teng, H.C. (2007) 3D laser scanning and GPS technology for landslide earthwork volume estimation. Automation in Construction, 16(5), 657-663. Hashash, Y. M. and Finno, R. J. (2008) Development of new integrated tools for predicting, monitoring, and controlling ground movements due to excavations, Practice Periodical on Structural Design and Construction, Vol.13, No.1, 4-10. Hashash, Y., Oliveira Filho, J., Su, Y., and Liu, L. (2005) 3D laser scanning for tracking supported excavation construction, Geo-Frontiers 2005, 24-26 Kim, S. K., Seo, J. W. and Russell, J. S. (2011) Intelligent navigation strategies for an automated earthwork system. Automation in Construction, 21, 132-147. Lever, P. Wang, F. (1995) Intelligent Excavator Control System for Lunar Mining System. Journal of Aerospace Engineering, 8(1), 16-24. Marechal, L. (2009), Advances in octree-based allhexahedral mesh generation: handling sharp features, 18th International Meshing Roundtable, Salt Lake City, UT, USA, 65-84. Park, J. J., Shin, J. H., Hwang, J. H., Lee, K. H., Seo, H. J. and Lee, I. M. (2012) Assessment of over / under-break of tunnel utilizing BIM and 3D laser Scanner, Journal of Korean Tunneling and Underground Space Association, 14(4), 437-451. Park, S. H., Choi, D. H., Han, D. Y., (2009) Deformation Measurements of Dam using Terrestrial Laser Scanner, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol.27, No.1, 645-655. Pejić, M. (2013) Design and optimisation of laser scanning for tunnels geometry inspection, Tunnelling and Underground Space Technology, Vol.37, 199-206. Prokop, A. and Panholzer, H. (2009) Assessing the capability of terrestrial laser scanning for monitoring slow moving landslides", Natural Hazards and Earth System Science, Vol.9, No.6, 1921-1928. Saxena, M., Finnigan, P. M., Graichen, C. M., Hathaway, A. F. and Parthasarathy, V. N. (1995), Octree-based automatic mesh generation for non-manifold domains, Engineering with Computers, Vol. 11, 1-14.

Singh, S. (1997) State of the art in automation of earthmoving. Journal of Aerospace Engineering, 10(4), 179-188. Slattery, K., Slattery, D., and Peterson, J. (2012). Road Construction Earthwork Volume Calculation Using Three-Dimensional Laser Scanning, Journal of Surveying Engineering, Vol.138, No.2, 96-99. Wulf, T. A., Wit, B., Carlier, L., Ryck, M. and Baker, H. (2010) High resolution terrestrial laser scanning for tunnel deformation measurements, FIG Congress.