CAD-based Laser Scan Planning System for Complex Surfaces

Transcription

1 CAD-based Laser Scan Planning System for Complex Surfaces Kwan H Lee, Seokbae Son, and Hyunpung Park Kwangju Institute of Science and Technology (K-JIST), Korea lee@kyebekkjistackr, sbson@kjistackr, and baram@kyebekkjistackr ABSTRACT In this research, we propose an automated measuring system for a complex freeform surface In order to automate a measuring process, appropriate hardware system as well as software modules are required The hardware system consists of a laser scanning device and setup fixtures that can provide proper location and orientation The software modules generate optimal scan plans and the scanning operation is performed accordingly In the scan planning step, various scanning parameters are considered 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 captured automatically The measured point data is registered automatically and the quality of point data is evaluated by the difference between the CAD model and the measured data Keywords: automated scanning, laser scanner, optimal scan plan, reverse engineering 1 INTRODUCTION More and more products with complex freeform surfaces are developed to meet the aesthetic requirements of consumers these days The part that has a freeform surface is usually developed through the reverse engineering process Acquiring the shape data of a physical part is an essential process in reverse engineering The quality of the reconstructed surface model depends on the type and accuracy of measured point data, as well as the type of a measuring device [1, 3] Currently, a CMM (Coordinate Measuring Machine) and a three-dimensional laser scanner are widely used in the fields for reverse engineering and inspection Since a CMM acquires point data by touching a probe to a part, it is appropriate for measuring primitive features that need only a small number of point data Laser scanners, however, can get a large amount of point data by a non-contact method in a short time Therefore, they are suitable for measuring freeform surfaces [1] In laser scanning of complex 3D parts, it is difficult to determine the number of necessary scans, the directions of scans and scan paths since the device has optical constraints [2,3,4,5,6,14] In order to resolve problems in manual scanning, an automated measuring system, in which scan plan generation and scanning are performed automatically, is needed [10,11,12,15] In this research, an automated scanning system for a freeform surface is developed The system can generate an optimal scan plan, which includes the number of required scans, the scan directions, and the scan paths considering various parameters of the equipment based on the proposed algorithms In order to implement an automated system, automated part setup is necessary, and a motorized rotary table is used for this purpose The generated scan paths are then downloaded to the laser scanner and the scanning operation is performed The captured point data is registered automatically and the quality of the point data is analyzed to prove the scanning system 11 Basics of the Laser Scanning System The mechanism of the 3D laser scanner used in this research is illustrated in Fig 1 A laser stripe is projected onto a surface and the reflected beam is detected by CCD cameras Through image processing and triangulation method, three-dimensional coordinates are acquired The laser probe is mounted onto a 3-axis transport mechanism and moves along the scan path that consists of a series of predetermined line segments

2 Laser Probe SENSOR 0 Laser Stripe Laser Beam SENSOR 1 Z X part Y Fig 1: Laser Scanning Mechanism 12 The Scope of Research The final goal of this research is to scan a part with freeform surfaces automatically with minimum human intervention The whole process consists of three parts; scan plan generation, scanning, and registration/analysis (Fig 2) Scan plan generation Scanning Registration and analysis Estimating scan directions Part setup and calibration Registration and localization CAD model Generating scan paths Coordinate transformation Error analysis Checking DOF and occlusion Automated scanning Reporting Fig 2: Overall procedure In the scan plan generation step, the optimal scan plan is calculated considering various measuring constraints The scan plan includes the number of required scans, the scan directions, and the scan paths [7,11,12] In this research, it is assumed that the CAD model of the part is available For calculating the optimal scan plan, we propose algorithms using the methods of estimation and modification In order to scan the part along the generated scan plan, appropriate part setup and the coordinate transformation of the scan paths should be performed For scanning, the part is setup using a motorized rotary table with two axes, and the coordinate transformation is done by a combination of the translation and rotation matrices After the calculated scan paths are downloaded to the scanner, scanning of the part is executed After scanning is completed, the acquired data from different scan directions should be aligned in one coordinate system, which is called registration [3,8,9,] In this research, registration is done automatically because the transformation matrices can be handled by using the rotation angles of the rotary table Finally, the difference between the CAD model and the scanned data is calculated and the quality of the scanned data is verified [13] 2 SCAN PLAN GENERATION 21 Overall Procedure Since a laser scanner consists of optical sensors and mechanical moving parts, various constraints should be satisfied when measuring a certain point on a part The important constraints are as follows: (1) View Angle: The angle between the incident beam and the surface normal of the point should be less than a certain value

3 (2) Field of View (FOV): The point should be located within the length of a laser stripe (3) Depth of Field (DOF): The point should be within a specified range of distance from the laser source (4) Occlusion: The incident beam as well as the reflected beam should not be interfered with by the part itself (5) The laser probe should travel along a path that is collision-free The overall procedure of scan plan generation is shown in Fig 3 and the detail of each module will be explained in following sections Sampling points on the surface Finding critical points Grouping sampled points based on critical points Generating initial scan directions Calculate minimum bounding box Generating scan path Checking depth of field and occlusion Modify or add a scan direction? NO Generate final scan plan YES Fig 3: Overall procedure for the generation of a scan plan 22 Determination of the Initial Scan Direction In order to scan two points together, the angle made by the normal vector at each point should be less than twice the view angle The points that do not satisfy the constraint are referred to as critical points and the required number of scans is estimated based upon the critical points After finding all critical points, those that have a lower angle deviation in their normal vectors than the view angle are grouped The number of groups represents the required number of scan directions The next step is to calculate the initial scan directions based on the groups of critical points First, the maximum deviation points, C 1-1 and C 2-1, those that have the maximum angle deviation in their normal vectors, are determined among the critical points (Fig 4) Each region grows by finding all the sampling points whose normal vector has an angle deviation smaller than the user-defined angle with respect to the maximum deviation point Finally, the global mean of all the normal vectors at the points in the group is determined as an initial scan direction Initial Scan Direction 2 Region 2 Maximum critical point C 2-1 Initial Scan Direction 1 Region 1 Maximum critical point C 1-1 Sampling point : Critical points set 1 : Critical points set 2 Fig 4: Conceptual drawing for generating an initial scan direction

4 23 Scan Path Generation The scan path is the collection of line segments that guide the laser probe during scanning In order to reduce the scanning time, the length of the total scan path and number of scan paths should be minimized First, the sampling points that can be scanned in the same scan direction should be grouped respectively (See Fig 5) Then the point sets should be projected onto a 2D plane that is perpendicular to the scan direction Secondly, the bounding rectangle with the smallest area should be calculated In order to compensate for possible errors caused by approximation, the bounding rectangle should be offset Since the direction of the laser stripe and scan path are parallel with the y-axis and x-axis, respectively, the edges of a bounding rectangle are also parallel with the y-axis and x-axis The width of a sub-rectangle along the y-axis is 1~2mm shorter than the length of the laser stripe to ensure the data acquisition of the boundary and to facilitate the surface fitting operation Scan path Projected sampling point l stripe /2 Laser stripe length, l stripe Y Minimum bounding rectangle X Fig 5: An example of scan path generation 24 DOF and Occlusion Checking After generating the scan path, DOF and occlusion constraints have to be checked to verify the scan direction To check the DOF, the laser beam is simplified as five lines as shown in Fig 6(a) If all points where the beam contacts the surface are located in the DOF region, the region can be scanned Occlusion checking is illustrated in Fig 6(b) If the sides of the triangle interfere with the surface, an occlusion exists For more reliable results, it is assumed that a point is scannable only when the reflected beam reaches both sensors of the probe When a part is setup as in Fig 1, the unscannable points due to the violation of the DOF condition can be scanned by rotating the scan direction about the x-axis (Fig 6(a)) Whereas, unscannable points due to occlusion can be scanned by rotating the scan direction about the y-axis (Fig 6(b)) Some points are unscannable due to the violation of both conditions, which requires the rotation of both axes For all unscannable points, if the directions of rotation conflict with each other, then a new scan direction must be added Probe Sensor 0 Sensor 1 "! Z Inscannable Point Y DOF region (a) (b) Fig 6: Modifying scan direction (a) due to a DOF problem and (b) due to an occlusion problem Z X

5 3 AUTOMATED LASER SCANNING 31 Laser scanning System and Part Setup The automated scanning system is implemented using a laser scanner and a motorized rotary table Figure 7 shows the configuration of the scanning system In order to scan a part from any direction, the system must have six degrees of freedom Since the laser scanner has four degrees of freedom, the remaining two degrees of freedom are provided by a rotary table The specifications of the laser scanner is listed in Table 1 In order to verify the software and the scanning system developed in this research, a test part is designed and prepared by machining an aluminum work piece The test part consists of a complex freeform surface and five planar surfaces (Fig 8) Fig 7: The laser scanning system Fig 8: The test part Table 1: Specification of the 3D laser scanner (SURVEYOR Model 2030, Laser Design, Inc) Parameters Values Standoff distance 149 mm View angle 80 degrees Depth of view 40 mm Field of view (middle) 32 mm Laser stripe length 15 mm Sample count 240 points/line Beam width 0254 mm Fig 9: Setup of a fixture and a rotary table In automating the scanning and the registration of the captured point data, a part setup process is necessary The test part should be positioned on the motorized rotary table For the localization process, sensing devices, a laser scanner, a tooling ball, and a dial indicator are required First, each axis of the rotary

6 table should be aligned with the axis of the laser scanner using the dial indicator mounted on the laser scanner Secondly, a specially designed fixture is attached to the rotary table and also positioned The test part will be placed inside of the fixture Figure 9 shows the alignment process of the fixture using the dial indicator The relationship between each axis of the rotary table and specifications are already known Therefore, in order to localize the test part, at least two centers of rotation of the rotary table are required In this study, the rotary table is rotated about the X-axis and Z-axis An accurate tooling ball is scanned several times while rotating the rotary table about X-axis and Z-axis After preparing transformation values, the scan paths should be mapped onto the coordinate system of the laser scanner 32 Scan Path Generation In this research, the scan plan is generated using the scan path generation module Fig 10(a) shows the surface model of the test part and Fig 10(b) shows the generated scan directions and paths graphically Fig 10(c) shows the screen dump of the result of scan plan and the scan plan will be translated and downloaded into the scanning system [16] Scan direction 1 Scan direction 2 Required # of Scans : 2 Scan 1 : Direction: , , Scan Paths: From: , , To: , , From: , , To: , , From: , , To: , , From: , , To: , , From: , , To: , , From: , , To: , , Scan 2 : Direction: , , Scan Paths: From: , , To: , , From: , , To: , , From: , , To: , , From: , , To: , , From: , , To: , , From: , , To: , , (a) (b) (c) Fig 10: Generated scan plan (a) the surface model with normals (b) scan directions and paths (c) screen dump of scan path The scan paths have to be mapped into the coordinate system of the laser scanner because the developed surface modeler and the laser scanner have their own separate coordinate system (Fig 11) The angle of rotation for each axis and the translation value used for the coordinate transformation are calculated from the scan direction and the measured coordinate information Zmodel Zscanner Yscanner Rotation and Translation Xmodel Surface modeler Ymodel Fig 11: Coordinate transformation Laser scanner Xscanner

7 The coordinate transformation matrix is as follows: [ M ] = [ T ] [ R] [ R] Rotary table Rotary table Modeler θ X axis φ Y axis where the matrix [ T ] Modeler translates the scan paths from the modeler axis to the rotary table axis and the θ matrix [ R] X rotates the scan paths by θ along the X-axis Therefore, the final scan paths can be calculated axis using the matrix [M] as follows: [ Final Scan Paths ] = [ Scan Paths ] Modeler [ M ] where the matrix [ Scan Paths ] is the generated scan paths in the scan path generation module Modeler 33 Automated Scanning and Registration Most measuring systems have their own scanning software and file format It is therefore necessary to translate the scanning plan into a specific file format that the scanning system can read After downloading the translated scan plan into the laser scanning system, an automated scanning operation of the test part is performed The test part is scanned in two directions and the total scanning time is about 10 minutes, with 05mm steps After scanning the whole surface, the scanned point data is registered in a one coordinate frame to reconstruct a surface model (Fig 12) The registration process can be performed automatically because the axis information is already known The automated registration process can save much time and replace tedious data processing work But the acquired point data is very large, and it is necessary to reduce it using the space sampling method before further surface modeling and NC code generation Fig 12: The registered scan data 33 Data Localization and Analysis In this system, the data localization process is performed automatically using the coordinate transformation method In figure 13, the curve-net model is designed in the CAD system and the point data is scanned by the laser scanner Figure 14 shows the result of data localization between the measured point data and the CAD model for the upper surface + = Measured data CAD model Localized model Fig 13: Data localization

8 Fig 14: Result of data localization The scanned point data usually includes errors from the moving system, the sensor and the positioning system In order to verify the accuracy of the laser scanning system and the registration process, the deviation between the nominal CAD model and the measured point data at each point is directly calculated in this study The distance map gives a clear measuring error range for the part The measuring error is estimated using the Surface-Cloud Difference method [17] The results of error estimation are shown in Table 2 There were only a few points that have a large deviation from the surface model Therefore, it can be expected that the average deviation and standard deviation will be relatively small Those points that have large deviations are easily removed by using a colored deviation map, which will improve the quality of the measured data Table 2: Result of error analysis between the CAD model and captured data (Unit: mm) Maximum deviation Average deviation Standard deviation Positive value Negative value CONCLUSION In this paper, an automated laser scanning system is proposed The system can automatically generate a scan plan by investigating a complex freeform part The scan plan includes the number of scans, the scan directions and the scan paths Also, the angle of rotation and the translation value used for the coordinate transformation are extracted from the scan direction information Using these values, the part can automatically be positioned and scanned precisely in a short time by a motorized rotary table The automated part positioning system can save much time and improve the quality of captured data Also, the registration process is simplified, redundant data processing is drastically reduced, and errors caused by human operator are minimized 5 ACKNOWLEDGEMENT This work was supported by grant No from the Basic Research Program of the Korea Science and Engineering Foundation 6 REFERENCES 1 Tamas Varady, Ralph R Martin and Jordan Cox, Reverse Engineering of Geometric Models An Introduction, Computer Aided Design, Vol 29, No 4, pp , F Xi and C Shu, CAD-based path planning for 3-D line laser scanning, Computer-Aided Design, Vol 31, pp , K H Lee, H Park and S Son, A Framework for Laser Scan Planning of Freeform Surfaces, International Journal of Advance Manufacturing Technology, Vol 17, pp , A Bernard and M Véron, Analysis and Validation of 3D Laser Sensor Scanning Process, Annals of the CIRP, Vol 48/1/1999

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