automated laser scanning system for reverse engineering and inspection

International Journal of Machine Tools & Manufacture 42 (2002) 889–897

Automated laser scanning system for reverse engineering andinspection

Seokbae Son, Hyunpung Park, Kwan H. Lee∗

Department of Mechatronics, Kwangju Institute of Science and Technology (K-JIST), 1 Oryong-dong, Puk-gu, Kwangju, 500-712, South Korea

Received 30 August 2001; received in revised form 5 March 2002; accepted 6 March 2002

Abstract

Recently, laser scanners have been used more often for inspection and reverse engineering in industry, such as for motors,electronic products, dies and molds. However, due to the lack of efficient scanning software, laser scanners are usually manuallyoperated. Therefore, the tasks that involve inspection and reverse engineering processes are very expensive. In this research, wepropose an automated measuring system for parts having a freeform surface. In order to automate a measuring process, appropriatehardware system as well as software modules are required. The hardware system consists of a laser scanning device and setupfixtures that can provide proper location and orientation for the part to be measured. The software modules generate optimal scanplans so that the scanning operation can be performed accordingly. In the scan planning step, various scanning parameters areconsidered in the generation of optimal scan paths, such as the view angle, depth of field, the length of the stripe, and occlusion.In the scanning step, the generated scan plans are downloaded to the industrial laser scanner and the point data are capturedautomatically. The measured point data sets are registered automatically and the quality of point data is evaluated by checking thedifference between the CAD model and the measured data. To demonstrate an automated measuring system, a motorized rotarytable with two degrees of freedom and a CNC-type laser scanner with four degrees of freedom are used. 2002 Elsevier ScienceLtd. All rights reserved.

Keywords: Automated scanning; Laser scanner; Optimal scan plan; Reverse engineering

1. Introduction

While a conventional engineering process starts witha design concept, in reverse engineering, a product isdesigned by capturing the shape of the real part. Thepart that has a freeform surface is usually developedthrough the reverse engineering process. Acquiring theshape data of a physical part is an essential process inreverse engineering. The quality of the reconstructed sur-face model depends on the type and accuracy of meas-ured point data, as well as the type of measuringdevice [1,2].

Currently, a CMM (coordinate measuring machine)and a three-dimensional (3D) laser scanner are widelyused in the fields for shape reverse engineering and qual-

∗ Corresponding author. Tel.:+82-62-970-2386; fax:+82-62-970-2384.

E-mail address: [email protected] (K.H. Lee).

0890-6955/02/$ - see front matter 2002 Elsevier Science Ltd. All rights reserved.PII: S0890-6955 (02)00030-5

ity inspection. Most CMMs use a trigger-type probe, butthe ones with mechanical analogue scanning probe doexist. The trigger-type CMM acquires point data bytouching the probe to the part, such that it is appropriatefor measuring primitive features that need small numberof point data. The scanning-type CMMs can capturemore sampling points than the touch trigger-type andhave better accuracy than vision sensors. They can beused for measuring freeform features [3], however, theycannot measure a part made of soft materials and haverelatively lower scanning speed compared to laser scan-ners. Laser scanners, on the other hand, can obtain alarge amount of point data by non-contact method in ashort time. Since the accuracy of the laser scanner isgetting improved, they are widely adopted for manyapplications in industry.

In laser scanning of complex 3D parts, it is difficultto determine the number of necessary scans, the direc-tions of scans and scan paths since the device has severaloptical constraints such as depth of field (DOF), field of

890 S. Son et al. / International Journal of Machine Tools & Manufacture 42 (2002) 889–897

view (FOV), and self-occlusion [4,5,6,16]. It takes muchtime and cost due to trial and errors when the parts arescanned manually. In order to resolve this problem, anautomated measuring system, in which scan plan gener-ation and scanning are performed automatically, isneeded [9,10,17]. Moreover, for scanning the reflectiveor transparent materials, preprocessing with a properspray is required.

In this research, an automated scanning system forreverse engineering and inspection of a freeform surfaceis developed. The system can generate an optimal scanplan, which includes the number of required scans, thescan directions, and the scan paths considering variousparameters of the equipment. In order to implement anautomated system, automated part setup is necessary,and a motorized rotary table is used for this purpose.Upon measuring, the axes of the rotary table are known,and the table is automatically rotated to orient the partexactly. The generated scan paths are then downloadedto the laser scanner and the scanning operation is perfor-med. The captured point data is registered automaticallyand the quality of the point data is analyzed.

2. Background and research scope

2.1. Basics of laser scanning system

The mechanism of the 3D laser scanner used in thisresearch is illustrated in Fig. 1. A laser stripe is projectedonto a surface and the reflected beam is detected by CCDcameras. Through image processing and triangulationmethod, three-dimensional coordinates are acquired. Thelaser probe is mounted on a three-axis transport mech-anism and moves along the scan path that consists of aseries of predetermined line segments. It also rotates intwo directions.

When the laser scanner captures an image, the systemautomatically finds an optical focus and keeps the stand-off distance. The length of laser stripe and the stand-off

Fig. 1. Laser scanning mechanism.

distance cannot be changed by an operator. Since a laserscanner consists of optical sensors and mechanical mov-ing parts, various constraints must be satisfied whenmeasuring a certain point on a part (Fig. 2). The goal ofthis section is to generate an optimal scan plan that satis-fies the following major constraints [6]:

1. View angle: the angle between the incident laserbeam and the surface normal of a point being meas-ured should be less than the maximum view angle g

di�Ni�cos(g),

where

di �L�Pi

|L�Pi|.

2. FOV: the measured point should be located within thelength of a laser stripe

(�di)�Bi�cos�d2�,

where d is the FOV angle3. DOF: the measured point should be within a specified

range of distance from the laser source

lSTAND�lDOF

2�|L�Pi|�lSTAND �

lDOF

2,

where lSTAND and lDOF denotes stand-off distance andDOF length.

4. Occlusion: the incident beam as well as the reflectedbeam must not interfere with the part itself.

5. The laser probe should travel along a path that is colli-sion-free.

6. If the part is shiny or transparent, preprocessing isrequired such as spraying.

Fig. 2. Constraints for laser scanning.

891S. Son et al. / International Journal of Machine Tools & Manufacture 42 (2002) 889–897

2.2. The scope of research

The final goal of this research is to scan a part withfreeform surfaces automatically with minimum humaninteraction. The whole process consists of three parts:scan plan generation; scanning; and registration/analysis.

In the scan plan generation step, the optimal scan planis calculated considering various measuring constraints.The scan plan includes the number of required scans, thescan directions, and the scan paths [11,12]. In thisresearch, it is assumed that the CAD model of the partis available. For calculating the optimal scan, we proposealgorithms using the methods of estimation and modifi-cation.

In order to scan the part along the generated scan plan,problems with the part setup and the coordinate trans-formation of the scan paths should be investigated. Forscanning, the part is setup using a motorized rotary tablewith two axes, and the coordinate transformation is doneby a combination of the translation and rotation matrices.After the calculated scan paths are downloaded to thescanner, scanning of the part performed.

After scanning is completed, the acquired data fromdifferent scan directions should be combined in onecoordinate system, which is called registration [2,14,15].Conventional registration method of using features suchas balls (or spheres) is very time consuming. In thisresearch, registration is done automatically using therotation angles of the rotary table. Finally, by calculatingdifferences between the CAD model and the scanneddata, the quality of the scanned data is verified.

Fig. 3 shows the overall procedure of the proposedautomated measuring system. The details of each partare explained in later sections.

2.3. Previous research

Although laser scanners have been widely used inrecent years, there exist few researches related to laserscanning. Some research works related to laser scanningare briefly summarized next.

Xi and Shu [4] developed a CAD-based path planningsystem for a 3D line laser scanner. They tried to maxim-ize the coverage of the part by finding the best setup for

Fig. 3. Overall procedure.

the field of view of the laser scanner and part orientation.However, the system focused on the parts with primi-tive features.

Bernard and Veron [5] developed a new method thatautomatically can scan a part using off-line program-ming of the CMM. To facilitate the data acquisition pro-cess, a software module called the Paint was used tofind the illuminated region by the laser beam. The sys-tem, however, needed to be improved in terms of itsscanning efficiency for a complex part.

Zussman et al. [6,7] developed an algorithm thatdetermined the location of a laser sensor. But their algor-ithm was only applicable to a 2D profile of a surfaceand could not be used to scan an entire surface of anobject. Elber and Zussman [8] developed an algorithmthat can calculate the number of scans and correspondingoptimal scanning directions for a part with a freeformsurface using a surface decomposition method. Theyonly considered the angle between the surface normaland the incident beam in determining the scannability ofa point on a surface, and did not consider other con-straints.

CMMs have been widely used in industrial appli-cations and some parts of the measuring processes aresimilar to that of laser scanners. Among many researchactivities, some notable works are described below. Yauand Menq [9] and Lim and Menq [10] developed anautomated CMM path planning system for the inspectionof a complex part. The system gave collision-freeinspection paths for dies and molds. After the initial scanpath generation, the inspection plans were simulated ina CATIA robotics module using the ‘Verify’ program.The inspection of a manufactured part can be plannedin the CAD/CAM environment and executed by theCMMs in the shop floor automatically.

Spitz et al. [11] introduced the notions of accessibilityand approachability, and described two sets of algor-ithms for computing accessibility information. Onealgorithm performed exact computation on polyhedralobject and was relatively slow, whereas the other useddiscrete approximation for increasing the speed. Thediscretized algorithm has been tested on real-world parts.


3. Scan plan generation

3.1. Overall procedure

For a scan plan generation, a complex part must besegmented into functional surfaces and the scan plan willbe generated for each surface path. Instead of dealingwith the entire surface, the surface is approximated bya point set sampled from the surface, and scanning ofall sampled points by the minimum number of scans isthe final goal of this algorithm. Using the sampledpoints, pairs of points that cannot be scanned togetherare obtained and are used for estimating the necessarynumber of scans by considering the view angle con-straint. The intial scan plan, including the scan directionsand scan paths for each scan direction, is generated, thenthe DOF and occlusion constraints are tested. If somepoints cannot be scanned, an additional direction or amodified direction is calculated according to the geo-metric shape. For these new directions, the same pro-cedures are repeated until a final scan plan is generated.Fig. 4 shows the overall procedure for the generation ofa scan plan.

3.2. Determination of the initial scan direction

Since the number of sampled points affects the feasi-bility of a scan plan, a proper number of points shouldbe sampled. The distance between neighboring points isused as the criterion in the algorithm. That is, the dis-tance between neighboring sampled points must be lessthan the length of a laser stripe.

In order to scan two points in the same scan, the anglebetween the normal vectors of the two points should beless than two times the view angle. The points that donot satisfy the constraint are referred to as critical points.Since the existence of critical points means that the sur-face cannot be scanned at one time, the required numberof scans is estimated based upon the critical points. Afterfinding all critical points, those that have a lower angle

Fig. 4. Overall procedure for the generation of a scan plan.

deviation in their normal vectors than the view angle aregrouped. The number of groups represents the requirednumber of scan directions.

The next step is to calculate the initial scan directionsbased on the groups of critical point. First, the maximumdeviation points, C1–1 and C2–1, those that have themaximum angle deviation in their normal vectors, aredetermined among the critical points (Fig. 5). Eachregion grows by finding all the sampling points whosenormal vector has an angle deviation smaller than theuser-defined angle with respect to the maximum devi-ation point. This angle should be chosen considering thetrade-off between the sizes of the regions and the qualityof the scanned data. Finally, the global mean of all thenormal vectors at the points in the group is determinedas an initial scan direction. That is, the initial scan direc-tion is represented by

Initial scan direction ISDi � �n

j � 1

Dj /ni

where Dj is the unit normal vector of each samplingpoint and ni is the number of points in region i.

In general, the best scanning data is obtained whenthe scan direction and the surface normal vectors are par-allel to each other. The global mean direction minimizesthe angle difference between the scan direction and sur-face normals, such that it can be considered as the bestinitial scan direction. The concept of determination ofinitial scan direciton is illustrated in Fig. 5.

3.3. Scan path generation

The scan path is the collection of line segments thatguide the laser probe during scanning. The scan path ofthe laser scanner used in this research consists of asequence ID, a starting point, and an ending point. Gen-erally, high scannability depends on the length of thescan path, the number of scan paths, and the number ofsetup changes. In this algorithm, the length of the total

Fig. 5. Conceptual drawing for generating an initial scan direction.


Fig. 6. An example of scan path generation.

scan path and number of scan paths are minimized toachieve high scannability.

First, the sampling points that can be scanned in thesame scan direction should be grouped respectively (seeFig. 6). Then the point sets should be projected ontoa 2D plane that is perpendicular to the scan direction.Secondly, a bounding rectangle with the smallest area iscalculated. In order to compensate for possible errorscaused by approximation, the bounding rectangle shouldbe offset by lstripe/2. Since the direction of the laser stripeand scan path are parallel with the y- and x-axes, respect-ively, the edges of a bounding rectangle are also parallelwith the y- and x-axes. The width of a sub-rectanglealong the y-axis is 1–2 mm shorter than the length oflaser stripe to ensure the data acquisition of the boundaryand to facilitate the surface fitting operation.

The scanned area is the area swept by the laser stripealong the scan path. Therefore, all sampling pointsshould be included in the scanned area. Fig. 6 illustratesthis concept where the dotted rectangle represents thebounding rectangle of the sampling points and the solidrectangle represents the bounding rectangle of thescanned area.

3.4. DOF and occlusion checking

After generating the scan path, DOF and occlusionconstraints have to be checked to verify the scan direc-tion. To check the DOF, the laser beam is simplified asfive lines as shown in Fig. 7(a). If all points where thebeam contacts the surface are located in the DOF region,the region can be scanned.

Fig. 7. Modifying scan direction (a) due to a DOF problem and (b) due to an occlusion problem.

Occlusion checking uses a similar process comparedto with the algorithm used to check the DOF. In practice,a point can be scanned as long as the reflected beamreaches either one of the sensors. However, for morereliable results, it is assumed that a point is scannableonly when the reflected beam reaches both sensors ofthe probe. The triangle connecting the two CCD camerasensors and the point to be scanned is used for occlusionchecking [Fig. 7(b)]. If either side of the triangle inter-feres with the surface, an occlusion exists.

For most smooth surfaces, the initial scan plan workswell. However, when the scan plan is not feasible, afeedback algorithm should be applied to remedy theproblems. The feedback algorithm determines the policyconsidering the shape of the region where the problemoccurs.

When a DOF or an occlusion problem occurs, itshould be examined whether the unscannable points canbe scanned using the other scan directions in the scanplan. If so, the initial scan plan is still valid. If thesepoints cannot be scanned using any other directions, thescan direction should be modified, or an additional scandirection should be created.

When a part is setup as in Fig. 1, the unscannablepoints due to the violation of the DOF condition can bescanned by rotating the scan direction about the x-axis[Fig. 7(a)]. Whereas, unscannable points due toocclusion can be scanned by rotating the scan directionabout the y-axis [Fig. 7(b)]. Some points are unscannabledue to the violation of both conditions, which requiresthe rotation of both axes. For all unscannable points, ifthe directions of rotation conflict with each other, a newscan direction must be added.

After the modified direction or the new additionaldirection is determined, the same procedure that checksfor the scanning constraints is performed, and the feed-back loop is carried out until proper scanning plan isgenerated.


Table 1Specifications of the 3D laser scanner (SURVEYOR Model 2030,Laser Design, Inc.)

Parameters Values

Stand-off distance 149 mmView angle 80°Depth of view 40 mmField of view (middle) 32 mmLaser stripe length 15 mmSample count 240 points/lineBeam width 0.254 mm

4. Automated laser scanning

4.1. Laser scanning system and part setup

The automated scanning system is implemented usinga laser scanner (Surveyor model 2030, Laser DesignInc., see Table 1) and a motorized rotary table. Fig. 8shows the configuration of the scanning system. Thelaser scanner is a stripe-type device with three orthog-onal transportation axes and a rotating probe. In orderto scan a part from any direction, the system must havesix degrees of freedom. Since the laser scanner has fourdegrees of freedom, the remaining two degrees of free-dom are provided by a rotary table.

In order to verify the scan plan and the scan paths, atest part is designed and prepared by machining analuminum workpiece. The test part consists of a complexfreeform surface and five planar surfaces (Fig. 9). Thefreeform surface patch of the test part is intentionallydesigned so that it cannot be scanned at once run usinga three-axis CNC-type laser scanner.

In order to automate the scanning and the registrationof the captured point data, a part setup process is neces-sary. The test part should be positioned on the motorizedrotary table. For the localization process, sensingdevices, a laser scanner, a tooling ball, and a dial indi-cator are required. First, each axis of the rotary tableshould be aligned with the axis of the laser scanner using

Fig. 8. The laser scanning system.

Fig. 9. The test part.

the dial indicator mounted on the laser scanner. Sec-ondly, a specially designed fixture is attached on therotary table and is also positioned. The test part will belocated inside the fixture. Fig. 10 shows the alignmentprocess of the fixture using the dial indicator.

The relationship between each axis of the rotary tableand specifications are already known. Therefore, in orderto localize the test part, at least two centers of rotationof the rotary table are required. In this study, the rotarytable is rotated about the X-axis and Z-axis. An accuratetooling ball is scanned several times while rotating therotary table about the X- and Z-axes. The center ofrotation for each axis is calculated by fitting the centerpoints to a circle. The center of the tooling ball is alsocalculated by fitting the point data to a sphere. Conse-quently, every axis information for part localization isprepared. Then the scan paths generated in Section 3.3need to be mapped onto the coordinate system of thelaser scanner by using the information of the axes.

4.2. Coordinate transformation of scan paths

As mentioned above, the scan paths have to bemapped into the coordinate system of the laser scannerbecause the surface model has its own coordinate systemand the laser scanner also has own coordinate system

Fig. 10. Setup of a fixture and a rotary table.


(Fig. 11). In order to interface different systems, coordi-nate transformation is required. For the transformation,the angle of rotation for each axis and the translationvalue used for the coordinate transformation are calcu-lated from the scan direction determined in Section 3.2and the measured information in Section 4.1.

The coordinate transformation matrix is as follows[18]:

[M] � [T]Rotary tableModel [R]qX-axis[R]fY-axis

where the matrix [T]Rotary tableModel translates the scan paths

from the model axis to the axis of the rotary table andthe matrix [R]qX � axis rotates the scan paths by q alongthe x-axis.

Therefore, the final scan paths can be calculated usingthe matrix [M], and the matrix form of the transform-ation is as follows:

[Final scan paths] � [Scan paths]Model[M]

where the matrix [Scan paths]Model is the generated scanpaths in the scan path generation module. Consequently,the final scan paths, which are downloaded into the laserscanning system, are prepared.

4.3. Automated scanning and registration

Most measuring systems have their own scanningsoftware and file format. It is therefore necessary totranslate the scanning plan into a specific file format thatthe scanning system can read. The laser scanner used inthis study is operated by a proprietary software packagecalled DataSculpt and, therefore, the generated plan istranslated into the SCN binary file format [19].

The scan plan is generated using the scan path gener-ation module explained in Section 3.3. Fig. 12(a) showsthe surface model of the test part and Fig. 12(b) showsthe generated scan directions and paths graphically. Fig.12(c) shows the screen dump of the generated scan planand this scan plan is translated and downloaded into thescanning system.

After downloading the translated scan plan into thelaser scanning system, an automated scanning operationof the test part is performed. The upper surface of thetest part is sprayed with the white powder to preventunexpected reflection of the laser beam. The laser scan-

Fig. 11. Coordinate transformation.

ner uses a 15 mm-wide semiconductor laser probe andit can capture 240 points for each scan. The test part wasscanned in two directions and the total scanning timetook about 10 min, with 0.5 mm steps.

After scanning the whole surface, the scanned pointdata must be registered under one coordinate frame toreconstruct the whole surface model. This process canbe performed automatically because the axis informationis already known. As such, an automated registrationprocess can save much time by preventing it from tedi-ous data processing work. However, because the size ofacquired point data is very large, it is necessary to reduceit before further surface modeling and NC code gener-ation (Fig. 13).

4.4. Analysis of scanning data

The scanned point data usually includes errors fromthe moving system, the sensor and the positioning sys-tem. Errors are usually visualized using the changes ofcurvatures and normal vectors of the fitted surface [13].

In order to verify the accuracy of the laser scanningsystem and the registration process, the deviationbetween the nominal CAD model and the measuredpoint data at each point is directly calculated. The devi-ation map gives a clear measuring error range for thepart.

In order to analyze the quality of the measured pointdata, a data localization process has to be performed.Data localization places a measured point data in thesame reference as the CAD model. The concept of datalocalization is shown in Fig. 14. Typically the measureddata are moved to a target geometry or CAD model viadifferent types of data fitting methods such as the 3-2-1 fitting, the least square fitting, or the min–max fitting[14,15]. The selection of the data localization methoddepends on the shape of part and the required tolerance.

In this system, the data localization process is perfor-med automatically using the coordinate transformationmethod explained in Section 4.2 because the axisrelationship between the measured data and the CADmodel is already calculated. Fig. 15 shows the result ofdata localization between the measured point data andthe upper surface of the test part. In the figure, the curve-net model is designed in the CAD system and the pointdata is scanned by the laser scanner.

The measuring error is estimated using the surface-cloud difference [20]. The results of error estimation areshown in Table 2. There were few points which have abig deviation from the surface model. Therefore, it canbe expected that the average deviation and standard devi-ation will be relatively very small. Those points, whichhave big deviations, are easily removed by using a col-ored deviation map and it improves the quality of themeasured data.

Final error is the addition of all the error sources from


Fig. 12. Generated scan plan: (a) the surface model with normals; (b) scan directions; and paths (c) screen dump of scan path.

Fig. 13. The registered scan data.

Fig. 14. Data localization.

Fig. 15. Result of data localization.


Table 2The error between the CAD model and captured data (unit: mm)

Maximum Average Standarddeviation deviation deviation

Positive value 0.19817 0.05278 0.04087Negative value –0.18627 –0.05178 0.03894

the rotary table, the laser scanner, the fixture, the spraymaterial, the part setup method, etc. In order to increasethe accuracy of the measured data, selection of the scan-ning device, part setup, and scan plan generation areall important.

5. Conclusion

In this paper, an automated laser scanning system isproposed. The system can automatically generate a scanplan by investigating a complex freeform part whoseCAD model is given. The scan plan includes the numberof scans, the scan directions and the scan paths. Also,the angle of rotation and translation value required forthe coordinate transformation is extracted from the scandirection information. With these values, the part canautomatically be positioned and scanned precisely in ashort time using a motorized rotary table. The automatedpart positioning system can save much time and improvethe quality of captured data. Also, the registration pro-cess is simplified, thereby, redundant data processing isdrastically reduced and errors caused by human operatorcan be minimized.

The developed system is more applicable to inspectionthan to genuine reverse engineering because we assumedthat the CAD model of the part is given. So, in futurework, we will expand our system to unknown parts.

Acknowledgement

This work was supported by Grant No. 2000-1-30400-006-3 from the Basic Research Program of the KoreaScience and Engineering Foundation.

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automated laser scanning system for reverse engineering and inspection

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