180 Vol. 30 No. 2, pp , 2012 CPS-SLAM. Study on CPS-SLAM

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1 180 Vol. 30 No. 2, pp , 2012 CPS-SLAM Study on CPS-SLAM Improvement of Measurement Precision and Application for Tunnel Shape Measurement System Jeong Yongjin,YumiIwashita and Ryo Kurazume This paper presents a high precision 3D measurement system by multiple mobile robots. This system is composed of three mobile robots consisting of a parent robot and two child robots. The parent robot is equipped with a 3D laser scanner, attitude sensor and a total station, and the child robots are equipped with corner cubes. The parent robot moves and stops repeatedly, and measures the 3D shape using the equipped laser scanner at several positions. Meanwhile, the child robots also move and stop repeatedly, and act as mobile landmarks for the positioning of the parent robot. To improve the positioning accuracy, several devices were replaced or newly installed. The experimental results show the system achieves quite high accuracy of the 0.03% of target s size. As an example of applications, we applied the system to shape measurement of tunnels under construction, and verified that the accuracy of the developed system is as high as a high-precise 3D laser scanner. Key Words: Multiple Robots, Laser Measurement, 3D Map, Laser Range Finder, Information-oriented Construction 1. CPS-SLAM [1] ICT [2] [3] Kyushu University Fig. 1 3D laser measurement system, CPS-V Fig. 1 [1] [4] Cooperative Positioning System, CPS [5] JRSJ Vol. 30 No Mar., 2012

CPS-SLAM 181 GPS IMU 1 2 [6] [9] 2 [10] [13] 1 Leica ScanStation C10 TOPCON GLS-1500 2 GPS IMU 2 3 4 2. 2. 1 Fig.

4 Cooperative Positioning System, CPS [1] [5] Fig. 5 CPS 1 1 2 Fig.

2 CPS-SLAM 181 GPS IMU 1 2 [6] [9] 2 [10] [13] 1 Leica ScanStation C10 TOPCON GLS GPS IMU Fig TOPCON, GPT-9005A, Table 1 AS-21 1 SICK, LMS- 151, Table 2 1 ARS-136-HP 2 Applied Geomechanics Inc., MD-900-TS, Table 3 TOPCON A3 TOPCON, RC-3 Fig Fig. 4 Cooperative Positioning System, CPS [1] [5] Fig. 5 CPS Fig. 2 Table 3 The developed tunnel shape measurement system Table 2 Specification of LMS 151 (SICK AG) View angle Angular resolution Systematic error Statistical error Scanning frequency Max. range /0.5 ±30 [mm] ±12 [mm] 25 [Hz]/50 [Hz] 50 [m] Specification of MD-900-TS (Applied Geomechanics Inc.) Range ±25 Resolution Repeatability 0.01 (= 36 ) Hysteresis 0.02 (= 1 12 ) Table 1 Specification of GPT-9005A (TOPCON) Range 1.3 3, 000 [m] Angular resolution 0.5 /1 Accuracy (distance) ±2 [mm] + 2 [ppm] Distance Accuracy (angle) 1 Fig. 3 Scanning system by 1-axis laser range finder and rotating table

7 Coordinate transformation by CPS information for creating aligned 3D model 2 1 3 2 4 1 2 [1] CPS 10 [m] 323.9 [m] 0.97 [m] 0.

3 182 Fig. 6 3D measurement using CPS and laser range finder Fig. 4 Scanned 3D data in outdoor environment Fig. 5 Cooperative Positioning System, CPS Fig. 7 Coordinate transformation by CPS information for creating aligned 3D model [1] CPS 10 [m] [m] 0.97 [m] 0.30% [14] IMU ICP Iterative Closest Point [1] CPS Fig. 6 CPS Fig. 7 CPS 2. 2 CPS 0.30% 100 [m] 150 [mm] 1 AP-L1 TOPCON GPT-9005A TOPCON 2 LMS200 SICK LMS151 SICK 3 A5 TOPCON 18 [mm] A3 TOPCON 0 [mm] JRSJ Vol. 30 No Mar., 2012

CPS-SLAM 183 Table 5 Specification of internal attitude sensor in total station (GPT-9005A, TOPCON) Resolution 5 Max.

10 Flowchart of data collection measured by total station Table 4 Fig.

range ±4 [1] AP-L1 2 Applied Geomechanics, Inc., MD-900-TS, Fig. 8, Table3 2 2 2 AS-21 Fig.

4 CPS-SLAM 183 Table 5 Specification of internal attitude sensor in total station (GPT-9005A, TOPCON) Resolution 5 Max. range ±6 Fig. 8 Two-axes attitude sensor (MD-900-TS) and auto-leveling system (AS-21) Fig. 10 Flowchart of data collection measured by total station Table 4 Fig. 9 Auto-leveling system Specification of auto-leveling system (AS-21, Rizumu) Leveling accuracy ±10 Max. range ±4 [1] AP-L1 2 Applied Geomechanics, Inc., MD-900-TS, Fig. 8, Table AS-21 Fig. 8 9 Table 4 GPT-9005A Table 5 Fig l l tan 10 3l % 2 MD-900-TS [4] 3. Fig [m] 33 4, Fig. 12 Fig [mm] x 93 [mm] y 25 [mm] z 19 [mm] [m] 0.054% 0.3% [14] 343 [m] 5[m] 20 Fig. 14 Fig

5 184 Fig. 11 Photo of corridor Fig. 14 Measured shapes and errors in outdoor environment Fig. 15 Path of parent robots Fig. 12 3D model of corridor Fig. 16 Target tunnel Fig. 13 Measured shapes before and after a long distance movement 116 [mm] x 47 [mm] y 72 [mm] z 78 [mm] 0.034% 4. Fig [m] 0.3% Fig. 17 The design drawing of the tunnel 77.6 [m 2 ] Fig JRSJ Vol. 30 No Mar., 2012

CPS-SLAM 185 Fig. 18 Measurement experiment in tunnel Fig. 21 Shape comparison between the design and the measured shapes [mm] Fig.

6 Max. range 330 [m] Scanning speed 3,000 [points/s] Fig. 20 Obstacles in the tunnel Fig.

3,482,477 RMS error 32.2 [mm] Table 8 Errors against the measured shape by 3D laser scanner Number of points 2,808,262 RMS error 29.

6 CPS-SLAM 185 Fig. 18 Measurement experiment in tunnel Fig. 21 Shape comparison between the design and the measured shapes [mm] Fig. 19 Travel paths of the robots [m] Table 7 Specification of GLS-1000 (TOPCON) Range [m] Accuracy (distance) 4 [mm] (σ)/1 150 [m] Accuracy (angle) 6 Max. range 330 [m] Scanning speed 3,000 [points/s] Fig. 20 Obstacles in the tunnel Fig. 22 Shape comparison between measured shapes by 3D laser scanner and the proposed system [mm] Table 6 Errors against the design shape Number of points 3,482,477 RMS error 32.2 [mm] Table 8 Errors against the measured shape by 3D laser scanner Number of points 2,808,262 RMS error 29.6 [mm] 2 80 [m] Fig [m] Fig. 20 2[m] 2[m] [m] 17.5 [m] Fig. 21 Table 6 Fig [mm] 4. 2 Fig. 23 Histogram of errors TOPCON GLS-1000, Table 7 Fig. 22 Table 8 Fig. 23 Table 9 Fig [mm] 30 [m] 50 [mm]

7 186 Fig. 25 Fig. 24 Table 9 Cumulative distribution Error [mm] Ratio [%] Measured cross-section at 50 [m] position Zoom of measured cross-section at 50 [m] position 50 [mm] 50 [m] Fig % 50 [mm] [m] ±50 [mm] 30 [m] Fig [m] 17.2 [m] 2 MD-900-TS 5. CPS 80 [m] RMS 29.6 [mm] JST B [1] CPS SLAM vol.25, no.8, pp , [2] [3] [ 4 ] R. Kurazume, Y. Noda, Y. Tobata, K. Lingemann, Y. Iwashita and T. Hasegawa: Laser-based geometric modeling using cooperative multiple mobile robots, Proc. IEEE International Conference on Robotics and Automation, pp , [5] vol.13, no.6, pp , [6]T.Nuttens,A.deWulf,L.Bral,B.deWit,L.Carlier,M.de Ryck, C. Stal, D. Constales and H. de Backer: High resolution terrestrial laser scanning for tunnel deformation measurements, FIG Congress 2010, [ 7 ] M.J. Henriques and J. Casaca: Uncertainty in tacheometric measurement of convergences in tunnels, 3rd IAG / 12th FIG Symposium, [ 8 ] J.-S. Yoon, M. Sagong, J.S. Lee and K.-S. Lee: Feature extraction of a concrete tunnel liner from 3D laser scanning data, NDT&E International 42, pp , [ 9 ] S. Feketea and M. Diederichsa: Geotechnical and operational applications for 3-dimensional laser scanning in drill and blast tunnels, Tunnelling and Underground Space Technology, vol.25, no.5, pp , [10] S. Thrun, S. Thayer, W. Whittaker, C. Baker, W. Burgard, D. Ferguson, D. Haehnel, M. Montemerlo, A.C. Morris, Z. Omohundro, C. Reverte and W. (Red) L. Whittaker: Autonomous exploration and mapping of abandoned mines, IEEE Robotics and Automation Magazine, vol.11, no.1, pp.79 91, [11] K. Ishikawa, J. Takiguchi, Y. Amano, T. Hashizume and T. Fujishima: Tunnel cross-section measurement system using a mobile mapping system, Journal of Robotics and Mechatronics, vol.21, no.2, pp , [12] pp.a1a A28, [13] 28 DVD-ROM 2G2 7, [14] 8 cps-iii 16 pp , JRSJ Vol. 30 No Mar., 2012

8 CPS-SLAM 187 Jeong Yongjin 2010 Ryo Kurazume Yumi Iwashita 2007 Imperial College London Jet Propulsion Laboratory

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