( ) 2005 1
IC
1... 1 1.1... 1 1.1.1... 1 1.1.2... 1 1.2... 5 1.2.1... 5 1.2.2... 5 1.3... 7 2... 8 2.1... 8 2.1.1... 10 2.1.2... 11 2.1.3... 13 2.1.4... 13 2.2... 16 2.2.1... 19 2.2.2... 21 2.2.3... 23 2.2.4... 25 2.3... 30 2.4... 32 3... 33 3.1... 33 3.2... 41 3.2.1... 41 3.2.2... 46 3.3... 49 3.3.1... 61 3.3.2... 65 3.4... 73 3.5... 76 4... 77 i
... 78... 79 ii
1. 1... 6 2. 1... 9 2. 2... 12 2. 3... 15 2. 4... 18 2. 5... 18 2. 6... 20 2. 7... 22 2. 8... 24 2. 9... 27 2. 10... 28 2. 11... 29 2. 12... 29 2. 13... 31 3. 1... 35 3. 2... 35 3. 3... 36 3. 4... 38 3. 5... 39 3. 6... 39 3. 7... 40 3. 8... 43 3. 9... 44 3. 10... 45 3. 11... 45 3. 12... 47 3. 13... 47 3. 14... 48 3. 15 IC... 50 3. 16 IC... 51 3. 17()... 52 3. 18... 53 iii
3. 19... 54 3. 20 WebPC... 56 3. 21... 57 3. 22... 58 3. 23... 59 3. 24... 63 3. 25... 64 3. 26... 64 3. 27... 66 3. 28... 67 3. 29... 68 3. 30... 69 3. 31... 69 3. 32... 71 3. 33... 71 3. 34... 72 3. 35... 74 3. 36... 75 iv
1. 1... 4 3. 1... 51 3. 2... 52 3. 3 PA-10... 55 3. 4... 60 3. 5 IP7000BD... 62 3. 6... 72 v
1 1.1 1.1.1 [1][2][3] 1.1.2 2 (1) (2) 1
CAD Appearance Shape from shading (1) (2) 2
1 2 3 3 (1) (2) (3) 1.1 3
1. 1 4
1.2 1.2.1 1.2.2 1.1 2 5
1. 1 6
1.3 2 3 2 4 7
2 2.1 ( 2.1) 8
2. 1 9
2.1.1 [20][21] 10
2.1.2 [9] [10] [11][12] [13] 2.2 2.2(a)Cup (x1,y1) Dish(x2,y2) 2.2(b) [14] 11
Request Robot Vision System Please detect object positions on the table Responses Dish Cup (a) Request Robot Vision System Responses Cup: (x1,y1) Dish(x2,y2) Dish Cup (b) 2. 2 12
2.1.3 50~60Hz Shape from Shading [15] 2.1.4 QR [16][17][18]( 2.3) 13
[29] [19] 14
QR QR 2. 3 15
2.2 [7] 2.4 2.5 16
(a) (b) (c) (d) 17
2. 4 Robot Environment Requests Responses Responses Requests Vision System Requests Responses Requests Responses Human Objects 2. 5 18
2.2.1 2.6 LED 19
Human Request Responses Vision System Human Please Clear Off the Cup Cup Dish Dish (a) Human Request Responses Vision System Dish Cup Dish (b) 2. 6 20
2.2.2 2.7 1 21
Move Request Robot Vision System Responses Before Request Camera Image After Responses Dish Cup 2. 7 22
2.2.3 2.8 23
Environment Request Responses Room Light Vision System Blind Be Little Dark Close the Blind Window Dish Cup (a) Environment Request Responses Room Light Vision System Be Little Dark Blind Close the Blind Dish Cup (b) 2. 8 24
2.2.4 2 (A) 2.9 LED LED [22] (B) 2.10 2.11 IC ( 2.12) IC [23][24] 25
3 (A) (B) IC 26
Object Request Responses Vision System LED Light the Dish1 s LED Dish1 Cup Dish2 (a) Object Request Responses Vision System Light LED Dish Cup Dish (b) LED 2. 9 27
Request Object Vision System Responses TAG What kind of object exists? Dish Cup (a) Request Object Vision System Responses Name : Dish Weight : Dish Cup Name : Cup Weight : (b) 2. 10 28
Request Object Vision System Responses Localization Dish Cup Dish Cup (c) 2. 11 IC 2. 12 29
2.3 2.13 30
(a) (b) 2. 13 31
2.4 2.3 32
3 2 3.1 3.2 3.3 3.2 3.1 3.1 3.2 33
( 3.3) 34
3. 1 On-Line Off-Line 3. 2 35
Vision system Model matching Robot database Objects Environments 3. 3 36
IC [8] IC IC ( 3.4 3.5) 3.6) 2 ( 3.7) 37
3. 4 38
Vision system IC tag Robot database Objects Environments IC tag Information 3. 5 n m 3. 6 39
New Model Vision system Should be installed New Object Robot database Objects Environments IC tag Information 3. 7 40
3.2 IC 3.2.1 [4][5][6] ( 3.8)[25] 3.1 ( 3.10) 3.9 IC CAD IC 41
( 3.11) 42
3. 8 43
IC 3. 9 44
3. 10 3. 11 45
3.2.2 3.2.1 3.1(2) 3.12 3.13 3.14 IC CAD [26] IC 46
3. 12 Vision system download Manufacturer database Robot database IC tag Information Objects Environments 3. 13 47
Tag system Web server Web server Vision system Web server 3. 14 48
3.3 IC RFID(Radio Frequency Identification)( 3.15)[27] IC ( 3.16 3.1) ( 3.17) 3.2 3.18 3.19 7 PA-10A-ARM( 3.3)Omniscient Organizer NTSC CCD (Sony EVI370) TCP/IP PC/AT Web ( 3.20) XML 3.21 3.22 ( 3.23 3.4) RF-ID ID IC IC 49
3. 15 IC 50
3. 16 IC 3. 1 51
3. 17() 3. 2 52
Web server 3. 18 53
Network (TCP/IP) Camera Sony EVI370series Web Server Mitsubishi PA10 Vision agent Image processing board Hitachi IP7000 IC TAG Robot TAG Reader 3. 19 54
3. 3 PA-10 55
1 2 3 3. 20 Web PC PC Dell OptiPlex Dell Precision 56
Network (TCP/IP) Camera Sony EVI370series Web Server Mitsubishi PA10 Vision agent Image processing board Hitachi IP7000 IC TAG Requests Robot TAG Reader (a) Network (TCP/IP) Camera Sony EVI370series Web Server Mitsubishi PA10 Vision agent Image processing board Hitachi IP7000 IC TAG ID URL Robot TAG Reader (b) ID URL 3. 21 57
Network (TCP/IP) Camera Sony EVI370series Requests Object model Web Server Mitsubishi PA10 Vision agent Image processing board Hitachi IP7000 IC TAG Robot TAG Reader (c) Network (TCP/IP) Camera Sony EVI370series Web Server Mitsubishi PA10 Vision agent Image processing board Hitachi IP7000 IC TAG Robot R(x,y,z) TAG Reader (d) 3. 22 58
3. 23 80cm 100cm 20~30cm 59
3. 4 60
3.3.1 IP7000BD( 3.5) 3.24 WEB TCP/IP ( 3.25) ( 3.26) (1) [28] p q ( u, v) g( u, v) f ( u, v) g( u, v) f p N 2 u v u v u v r = p q p q 2 p q p q 2 (1) 2 2 N f ( u, v) f ( u, v) N g( u, v) g( u, v) u v u v u v u v r u x v y N r 0 1 q p q 61
3. 5 IP7000BD 62
Computer (PC) NTSC CCD 3. 24 63
(1) (2) (3) (4) 3. 25 3. 26 64
3.3.2 X V X R ( 3.27) 3.28 ( 3.29)(2)A ( 1 = ) = T V V T V R V R X X X X A AX X (2) = 1 1 1 2 2 2 1 1 1 Vn Vn Vn V V V V V V V z y x z y x z y x X M M M M (3) (4) = 1 1 1 2 2 2 1 1 1 Rn Rn Rn R R R R R R V z y x z y x z y x X M M M M 3.30 3.31 65
= / 1 Vn Vn V y x X = / 1 Vn Vn V y x X camera robot = / 1 Rn Rn Rn R z y x X = / 1 Rn Rn Rn R z y x X 3. 27 66
3. 28 67
3. 29 68
3. 30 (a) 100mm (b) 0mm (c) 100mm 3. 31 69
IC 3.32 (5) (6) z V WEB x z z x x z x z z x δ δ + = = + (5) = 1 1 1 2 2 2 2 2 2 2 1 1 1 1 1 1 1 Vn Vn Vn Vn Vn Vn Vn V V V V V V V V V V V V V V V z y z x z y x z y z x z y x z y z x z y x X M M M M M M (6) 3.33 15cm 9 11.78mm 2.25mm 9.88mm 1.81mm ( 3.34 3.6) 70
z h z 0 z x x x 3. 32 (a) 100mm (b) 0mm (c) 100mm 3. 33 71
3. 34 3. 6 11.78mm 9.88mm 2.25mm 1.81mm 72
3.4 3.35 3.36 73
3. 35 74
3. 36 75
3.5 2 RFID 2 76
4 (1) (2) 77
78
[1] S. T. Barnard and W. B. Thompson,: Disparity analysis of images, IEEE Trans. Pattern Analy. And Machine Intelligence, vol. PAMI-2, no. 4, pp.333-340, 1980 [2] T. Pavlidis, A review of algorithms for shape analysis, Computer Graphics and Image Processing, vol.7, pp. 243-258, 1978 [3] 3 VVV pp.2-4, 1998.6. [4] N. Y. Chong, H. Hongu, K. Ohba, S. Hirai, K. Tanie : Knowledge Distributed Robot Control Framework, Proc. Int. Conf. on Control Automation, and Systems, 2003. [5] N.Y. Chong, H. Hongu, K. Ohba, S. Hirai, K. Tanie, A Distributed Knowledge Network for Real World Robot Applications, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 187-192, 2004 [6] Manabu Miyazaki, Hiroshi Hongu, Nak Young Chong, Kohtaro Ohba, Shigeoki Hirai, Makoto Mizukawa, and Kazuo Tanie,: Knowledge Management Framework for the Knowledge Distributed Robot System, pp.237-240, First International Workshop on Networked Sensing Systems 2004 [7] 2002 [8] H. Hontani, M. Nakagawa, K. Baba, T. Kugimiya, and M. Sato,A, : Visual Tracking System using an ID-Tag, pp.183-186, First International Workshop on Networked Sensing Systems 2004 [9] Vol2,No6, pp89-94,1984 79
[10], SC-00-15, pp.25-30,, 2000.5 [11] - - Vol.12, No.5, pp.129-134 [12] Vol.20,No.4,pp14-18,2002 [13] J. Miura and Y. Shirai, Modeling Obstracles and Free Spaces for a Mobile Robot using Stereo Vision with Uncertainty, Proc. 1994 IEEE Int. Conf. on Robotics and Automat., San Diego, CA, USA, May. 1994 [14] Vol.34 No.6 pp.429-434 1995 [15] Zhang, R., Tsai,P.S.,Cryer, J.E., Shah, M.,: Shape from Shading : A Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, no. 8, pp. 690-706, 1999. [16] Rie KATSUKI, Jun OTA, Yusuke TAMURA, Takahisa MIZUTA, Tomomi KITO, Tamio ARAI, Tsuyoshi UEYAMA, and Tsuyoshi NISHIYAMA, : Handling of Objects with Marks by a Robot, Proceedings of the 2003 IEEE/RSJ Intl. Conference on Intelligent Robots and Systemus 2003 [17] C, 691, 70, 766/773 (2004). [18] 2004 pp. 85-86 2004 [19] (IMPS'99) I-2.15 pp. 41-42 (1999.9). [20] M. Takizawa, Y. Makihara, N. Shimada, and Y. Shirai, A Service Robot with Interactive 80
Vision -Object Recognition Using Dialog with User-, Proc. of the 1st Int. Workshop on Language Understanding and Agents for Real World Interaction, pp.16-23, 2003 [21] ID, HI104-4, 2003 [22] IMS 21 2003 [23] M.Boukra, S.Ando: Tag-based vision: assisting 3D scene analysis with radio-frequency tags, pp.269-272, ICIP02, 2002. [24] H. Hontani, K.Baba, T.kugimiya, M.Sato and Mnakagawa : Visual Tracking System using an ID-Tag and the Network, SICE Annual Conference 2003 in Fukui,2003. [25] Kim Bong Keun Chong Nak Young [26] Patrick J. Flynn, Anil K. Jain,: Cad-Based Computer Vision : From CAD Models to Relational Graphs, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, No.2, 1991 [27] Klaus Finkenzeller RFID 2001 [28] A. Gruen, and E. Baltsavias,: Adaptive least squares correlation with geometric constraints, Proc. Of SPIE, vol.595, pp.72-82, 1985 [29] 81