1234 Vol. 25 No. 8, pp , 2007 CPS SLAM Study on CPS SLAM 3D Laser Measurement System for Large Scale Architectures Ryo Kurazume,Yukihiro Toba

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1 1234 Vol. 25 No. 8, pp , 2007 CPS SLAM Study on CPS SLAM 3D Laser Measurement System for Large Scale Architectures Ryo Kurazume,Yukihiro Tobata,KoujiMurakami and Tsutomu Hasegawa In order to construct three-dimensional shape models of large-scale architectural structures using a laser range finder, a number of range images are normally taken from various viewpoints, and these images are aligned using post-processing procedures such as the ICP algorithm. However, in general, before applying the ICP algorithm, these range images must be registered to roughly correct positions by a human operator in order to converge to precise positions. In addition, range images must be made to sufficiently overlap each other by taking dense images from close viewpoints. On the other hand, if the positions of the laser range finder at viewpoints can be identified precisely, local range images can be directly converted to the global coordinate system through a simple transformation calculation. The present paper proposes a new measurement system for large-scale architectural structures using a group of multiple robots and an on-board laser range finder. Each measurement position is identified by a highly precise positioning technique called Cooperative Positioning System (CPS), which utilizes the characteristics of the multiple-robot system. The proposed system can construct 3D shapes of large-scale architectural structures without any post-processing procedure such as the ICP algorithm or dense range measurements. Measurement experiments in unknown and large indoor/outdoor environments are successfully carried out using the newly developed measurement system consisting of three mobile robots named CPS-V. Key Words: SLAM, 3D Map, Multiple Robots, Laser Range Finder, Digital Archive 1. SLAM Simultaneous Localization And Mapping [13] [15] SLAM SLAM SLAM Kyushu University 2 [1] [2] 1 ICP [4] [5] ICP JRSJ Vol. 25 No Nov., 2007

2 CPS SLAM 1235 ICP SLAM ICP GPS [6] [7] GPS RTK VRS GPS Cooperative Positioning System CPS [8] CPS CPS SLAM SLAM ICP GPS 1 2 SLAM 3 2 CPS [8] CPS 2. 1 CPS A B A B A B A B CPS Fig CPS 10 [m] Fig [m] Fig. 1 Cooperative Positioning System, CPS

3 1236 Fig. 2 Long distance measurement experiment (dr dφ dψ) T, d i = ( x 0 x i) 2 +(ỹ 0 ỹ i) 2 L = r 1 cos ψ 1 d 1 r 2 cos ψ 2 d 2 z 1 r 1 sin ψ 1 z 0 z 2 r 2 sin ψ 2 z 0 φ 1 + θ 0 tan 1 ỹ 1 ỹ 0 x 1 x 0 φ 2 + θ 0 tan 1 ỹ 2 ỹ 0 x 2 x 0 8 A R 6 4, K 1 R 6 8, K 2 R 6 3 L 0 7 Σ L = K 1ΣK T 1 + K 2Σ ΘK T 2 9 Fig. 3 Results of long distance measurement experiment Σ ( ) Σ11 Σ 12 Σ = 10 Σ 21 Σ [m] 0.3% [9] 2. 2 CPS CPS Fig. 1 3 CPS Fig. 1 (4) 0 2 P i(x i,y i,z i,θ i) (i =0 2) r 1 r 2 φ 1 φ 2 ψ 1 ψ (x 0 x 1) 2 +(y 0 y 1) 2 = r 2 1 cos 2 ψ 1 1 (x 0 x 2) 2 +(y 0 y 2) 2 = r 2 2 cos 2 ψ 2 2 z 0 = z 1 r 1 sin ψ 1 3 = z 2 r 2 sin ψ 2 4 θ 0 = φ 1 +tan 1 y 1 y 0 x 1 x 0 5 = φ 2 +tan 1 y 2 y 0 6 x 2 x 0 0 (x 0,y 0,z 0,θ 0) x i = x i + dx i Taylor Σ Θ Σ Θ = diag(σ 2 r σ 2 φ σ 2 ψ) 11 σr σ 2 φ σ 2 ψ 2 X 1,2 Θ 7 X 0 A X 0 Σ 1 L V = L AX 0 12 min V T Σ 1 L V 13 X X 0 0 X 0 X 0 =(A T Σ 1 L A) 1 A T Σ 1 L L = BL Σ 0 = BΣ LB T =(A T Σ 1 L A) AX 0 = L + K 1X 1,2 + K 2Θ 7 (Σ 01, Σ 02) =BK 1Σ 16 X 0 =(dx 0 dy 0 dz 0 dθ 0) T, X 1,2 = (dx 1 dy 1 dz 1 dθ 1 dx 2 dy 2 dz 2 dθ 2) T, Θ = i JRSJ Vol. 25 No Nov., 2007

4 CPS SLAM 1237 Fig. 1 (2) (3) x i = x 0 + r i cos φ i cos ψ i y i = y 0 + r i sin φ i cos ψ i z i = z 0 + r i sin ψ i x i = x i + dx i Taylor X i = L i + X 0 + K 2,iΘ 20 X i =(dx i dy i dz i dθ i) T Fig. 4 CPS SLAM with activetouchrobot L i = x 0 + r i cos φ i cos ψ i x i ỹ 0 + r i sin φ i cos ψ i ỹ i z 0 + r i sin ψ i z i 21 i X i = L i Σ ii = Σ 0 + K 2,iΣ Θi K T 2,i Σ 0i = Σ ij = Σ i P i X i P i P i + X i CPS σ r =3[mm] σ φ =5[s] σ ψ =5[s] 10 [m] 100 1[km] Σ 0 σx 2 + σy 2 = [m 2 ] [12] CPS SLAM CPS SLAM SLAM Simultaneous Localization And Mapping [13] [15] CPS SLAM Fig. 5 Obtained floor map CPS SLAM [10] Fig. 4 CPS Fig. 5 CPS SLAM CPS SLAM CPS ICP CPS CPS-V CPS-V CPS CPS-V Fig. 6 5 CPS CPS-V 1 P-cle Parent mobile unit Fig. 7 2 HPI Japan Fig. 8 LMS 200 Sick AP-L1 TOPCON Ltd. Table

1238 Fig. 6 Fifth CPS machine model, CPS-V Fig. 9 Indoor experiment using CPS-V Fig.

8 Child robot Table 1 Specification of total station, AP-L1 AP-L1 (TOPCON Ltd.

2[mm] Resolution (angle) 5 Precision (distance) 3 2ppm[mm] Precision (angle) 5 Table

) Range 80[m] Field of view 180 Resolution (distance) 10[mm] Resolution (angle) 0.

5 1238 Fig. 6 Fifth CPS machine model, CPS-V Fig. 9 Indoor experiment using CPS-V Fig. 7 3D laser measurement system using rotation table around yaw axis Fig. 8 Child robot Table 1 Specification of total station, AP-L1 AP-L1 (TOPCON Ltd.) Range 4 400[m] Resolution (distance) 0.2[mm] Resolution (angle) 5 Precision (distance) 3 2ppm[mm] Precision (angle) 5 Table 2 Specification of laser range finder, LMS200 LMS 200 (SICK Corp.) Range 80[m] Field of view 180 Resolution (distance) 10[mm] Resolution (angle) MD900-TS Applied Geomechanics Inc. 80 [m] 180 Table 2 Fig. 10 Path of parent robot yaw Fig CPS CPS CPS-V 1 4[m] Fig. 9 JRSJ Vol. 25 No Nov., 2007

6 CPS SLAM 1239 (a1) (a) (a2) Fig. 11 Obtained 3D map of indoor environment Fig. 10 x 39 [m] y 10 [m] 2 Fig Fig. 12 (a2) (b2) Fig. 12 (c2) CPS ICP CPS [m] 1.25 [m] 1.45% yaw CPS [9] Fig. 10 Corner 1 23 Fig. 13 (a) 1.17 [m] 1 2 CPS 1 Table 1 5[m] [12] 4[m] 2 22 CPS CPS CPS CPS (b1) (b2) (b) (c1) (c2) (c) Fig. 12 Obtained 3D map of indoor environment CPS [8] Fig CPS 93.9 [m] 0.22 [m] 0.24% yaw 1.5 Fig. 14 Corner Fig. 13 (b) 0.22 [m] Fig. 13 (a)

7 1240 (a) Child robot moves 22 times (b) Child robot moves 5 times Fig. 13 Comparison of modeling errors Fig. 15 Total view of 3D map in outdoor environment (a1) (a) (a2) (b1) (b) (b2) Fig. 14 Path of parent robot (each child robot moves 5 times) Fig Fig [m] 0.63 [m] 0.43% yaw 0.9 ICP [m] Fig. 18 Fig. 19 Fig (c1) (c2) (c) Fig. 16 3D map of buildings in outdoor environment [m] 0.80 [m] 0.61% yaw JRSJ Vol. 25 No Nov., 2007

18 Outdoor environment with slopes CPS CPS SLAM CPS CPS-V CPS

8 CPS SLAM 1241 Fig. 17 Path of parent robot Fig. 19 3D map of outdoor environment with slopes Fig. 18 Outdoor environment with slopes CPS CPS SLAM CPS CPS-V CPS ICP CPS ICP Fig. 20 Path of parent robot ICP B RT

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untitled 3,,, 3D laser measurement and map generation b cooperative multiple robots Yukihiro TOBATA, Ro KURAZUME, Kouji MURAKAMI and Tsutomu HASEGAWA Dept. of Intelligent Sstems, Graduate School of Information