Calibration of a Terrestrial Laser Scanner - Institute of Geodesy and ...

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acquisitiondescribingFinally, thatMainly,results.applicationways. The models by linemoving base objectcompleteddifferentmathematicalaregressionposition parametersestablishesseveral dataapplied andpointsThus,aKaimancalculatingpre-processingrequiredacquired methods processingto filter.wasorientationalsoexample forced motion2TPS1201 essential.trajectoryyieldof laserrunakinematicwith trolley from scanner anearly Leica were has constant Geosystemsdescribedestimated.velocity.126 6. Applications of Terrestrial Laser Scanningtrajectory is assessed by control points with coordinates derived analogous to the procedurethe use of the regression line, cf. Section 6.3.2.described for0 105£0 100 'rtf*M MfU^M^^^^^i^^^^j*J/1WW itaiArvpfip yvwilj¥ )\vy W\f y y0 09,5,„„44004450 4500 4550 4600 4650 4700 4750time tag [s]Figure 6.15: Velocity of moving trolley estimated by Kaiman filterforone data set.For example, the velocity of the test trolley of one data set estimated by the Kaiman filter is shown in Figure6.15. It can be seen that the motion of the trolleyoscillates. These oscillations are based either on the noiseproduced by the tracking total station or by the variations of the encoders controlling the velocityof thetest trolley. Considering a distance error of As 1mm by = a time interval of At 0.1s, = a variation inthe velocityof v = 0.01 results. Thus,with the distance accuracy of the total station.the oscillations of the velocity are relatively small in comparisonThe accuracy of the trajectory and the scanned point cloudis assessed by control points. The same parameters for the data sets are chosen compared to the examplewhere the regressionline was used. Table 6.3 summarizes the results and shows the 3D accuracy for thecontrol points. The accuracy is sufficiently high since the 3D accuracy is within 5 mm. Surprisingly, theaccuracy decreases with the time and therefore, with the length of the trajectory. One possibility is thatthe equidistant time tags of the total station measurements, derived for the Kaiman filter, show deviations.Another reason can be found in the Kaiman filter. The tuning of the filter, e.g. mathematical model ofthe system state, covariance matrices, offers several ways of deriving the trajectory. Considering the givenaccuracy of the used total station2 in the tracking mode (5 mm + 2 ppm), the 3D accuracy, given in Table 6.3,fits the manufacturer's specification.Furthermore, the same conclusion, as for the regression line, can be drawn: neither the rotation time nor thescan resolution significantly influence the 3D accuracy. Only the treatment of the diameter of the spheresincreases the accuracy.shown in Table 6.3.Changing the velocity to v = 0.2— and v = 0.3— have similar results, which are6.3.4 ResultsKinematic laser scanning has become an alternative to static laser scanning. The advantage is a higherperformance of scanning objects characterized by a fast acquisition rate. For linear objects, e.g.roads, kinematic applications are especially superior to static applications.tunnels orThe accuracy that can be achieved is not only limited bythe laser scanner used. The
6.3 Kinematic Application: Test Tunnel 127Table 6.3: Results of kinematic laser scanning based on the mathematical model of a Kaiman filter. The time, therotation per second (RPS), the scanning resolution, the number of control points and the 3D accuracyare shown.Time [s] RPS Scanning Resolution # Control Points 3D Accuracy [mm]'free''fix'100 2533200 2533300 2533middlehighmiddlehighmiddlehighmiddlehighmiddlehighmiddlehigh5 2.7 2.43.5 2.42.6 2.33.2 2.18 3.3 2.83.1 2.93.5 3.04.1 3.513 4.4 4.54.9 4.34.3 4.04.6 4.1The regression line represents optimal processing of the data since errors produced by processingthe dataare minimized. The total station data were only pre-processed with a median filter to eliminate blunders.The algorithm of the regression line allows for the calculation of a constant velocity of the trolley.residuals of the data used for calculating the regressionTheline confirm that the motion can be assumed to beconstant. The combination of both the test tunnel and the constant velocity of the test trolleyassessment of the stability of the rotation time of the rotatinginterpreted as sufficient regarding the 3D accuracy of the control points,'fix' adjustment.allows for anmirror of the laser scanner. The results can bewhich do not exceed 3 mm for theThe Kaiman filter is a powerful tool for estimating the trajectory of arbitrarily moving objects.Due to thecharacteristics of the sensors acquiring the required data for calculating the system state, additional pre¬processing algorithms have to be applied, such as polynomial interpolation and smoothing.The Kaimanfilter requires an appropriate mathematical model for the motion and the influencing variables disturbingthe motion. The filter tuning becomes a key factor and plays an important role. The results obtainedby Kaiman filtering refers to the filter settings.Kaiman filter.regression line.and covariance models.The implemented algorithm shows the feasibilityof theThe obtained 3D accuracy is slightly worse than the 3D accuracy obtained by applying theThe accuracy can be increased by testing more sophisticated filter settings,Nevertheless, the kinematic application of the laser scanner using the profilesuch as errormode has been successful.The obtained 3D accuracy of modeled objects does not exceed 5 mm. Thus, kinematic laser scanningconceivable for deformation monitoring in tunnel applications.is alsoThe laser scanner and its derived rotationtime offers a powerful instrument for the generation of a dense point cloud for kinematic applications. Forexample, the point cloud of the test tunnel along the calibration track line is shown in Figure6.16. Thecalculated point clouds have to be treated analogous to the point clouds based on static applications. Thismeans data processing and filter algorithms have to be appliednoise within the data, e.g. blunder detection and mixed pixels,to eliminate blunders and to reduce thecf. Section 4.1.The following figures show views of the processed laser scanning data. Figure 6.16 gives an impression ofa view inside the test tunnel.The track line on which the laser scanner moved runs along the right side.Since the laser scanner cannot acquire data below itself, due to the housing, the floor or objects lying underthe scanner were not captured bythe laser beam. Thecontrol points were visualized by sphereson the
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DISS. ETH NO. 17036Calibration of a
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ZusammenfassungSeit einigen Jahren
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ContentsAbstractiiiZusammenfassungv
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Contentsix6.1.3 Results Ill6.2 Stat
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1Introduction1.1 Terrestrial Laser
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1.2 Motivation 3Precision [m10~1 "1
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6 1. Introduction
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8 2. Components of Terrestrial Lase
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10 2. Components of Terrestrial Las
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24 3. Calibration of Terrestrial La
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'28 3. Calibration of Terrestrial L
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"[m] of system 90%) 3540 distance b
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!36 3. Calibration of Terrestrial L
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138 3. Calibration of Terrestrial L
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Inormal axis,intersectionpoint axis
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j/-*'.-,•66 3. Calibration of Ter
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74 4. Static Laser Scanning4.1.2 Mi
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Page 122 and 123: 112 6. Applications of Terrestrial
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Page 144 and 145: 134 7. Summary
Page 146 and 147: 136 A. Imaging System of Imager 500
Page 148 and 149: 138 B. Technical Data of Imager 500
Page 150 and 151: u140 C. Adjustment of SphereA =dfi,
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Page 154 and 155: 144 D. Electronic Circuit for Deter
Page 156 and 157: aMulti-SensorPlatform,PhDGeodesy Sw
Page 158 and 159: Accuracy-AeinTPS1200 AG, -Version 1
Page 160 and 161: -GenauigkeitsbetrachtungenInvestiga
Page 162 and 163: 152 BibliographyWunderlich, T. A. [
Page 164 and 165: List of Figures3.22 Residuals of th
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Page 168 and 169: 158 List of Tables
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