2
Right Image Left Image Pt-1 Pt Disparity : x L p t - x R p t Optical Flow : ( x R p t - x R p t-1 , y R p t - y R p t-1 ) 3DFlow : Pt - Pt-1 (x R p t-1 , y R p t-1 ) (x L p t-1 , y L p t-1 ) (x L p t , y L p t ) (x R p t , y R p t ) f (Pt) d (Pt-1) d (Pt)

A Ck-okada/paper/2000_rsj_okada_3...Oussama Khaib. Real-time obstacle av oidance for manipulators and mobile rob ots. International Journal of R ob otics R ese ar ch, V ol. 2, No

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Page 1: A Ck-okada/paper/2000_rsj_okada_3...Oussama Khaib. Real-time obstacle av oidance for manipulators and mobile rob ots. International Journal of R ob otics R ese ar ch, V ol. 2, No

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e]M[fIN\_KM[fYUQSMaf

�����ÿ����ü öú � � �� ûý� ø� þ� ÷� �ù

Walking Human Avoidance of Mobile Robot

Using A 3D Depth Flow and A Potential Feild

University of Tokyo *K.Okada T.Aoyama S.Kagami M.Inaba H.Inoue

Abstract : Three dimensional information of an environment is fundamentally important for a robot which moves

in real-world. This paper proposes 3D Depth Flow, which describes three dimensional structure and motion of a dynamic

environment, and an potential �eld based on 3D Depth Flow. Finally an experiment is shown, the robot avoids a few

walking persons using 3D Depth Flow based potential �eld.

Keywords : Moving Obstacle Avoidance, 3D Depth Flow, Potential Feild, PC-based Vision Processing

1 ����

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Right ImageLeft Image

Pt-1

Pt

Disparity : xLpt

- xRpt

Optical Flow : ( xRpt

- xRpt-1

, yRpt

- yRpt-1

)

3DFlow : Pt - Pt-1

(xRpt-1 , y

Rpt-1)

(xLpt-1 , y

Lpt-1)

(xLpt , y

Lpt )

(xRpt , y

Rpt )

f (Pt)

d (Pt-1)

d (Pt)

Fig. 1: A description of 3D Flow

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Page 2: A Ck-okada/paper/2000_rsj_okada_3...Oussama Khaib. Real-time obstacle av oidance for manipulators and mobile rob ots. International Journal of R ob otics R ese ar ch, V ol. 2, No

1A

R

2A

B

R

3A B

R

4A B

R

5 A B

R

6 A B

R

7 A

R

8 A C

R

9 A C

R

10 C

R

11 C

R

12 C

R

Fig. 3: Moving Obstacles Avoidance Experiment

(A) Image at t (B) Image at t� 1 (C) Depth image

(D) Optical ow (D) 3D Depth Flow

Fig. 2: A Result of 3D Depth Flow Generation

4.1.4 âàÒæ¹ïÍ 0#�èV¦4¢����¡&-�ý¡ÃÓw��',ô¦�X��t�æ¦ Fig.2s Table. 1�.�t0�� PentiumIII-750MHz (ë�Áµ 100MHz) ¦�|� linux 2.2.14 =����t 10[Hz]�6÷�&-�ý¡ÃÓw¦îw��£r

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Table 1: A Calculation Time of Each Function Of 3D

Depth Flow on PentiumIII-750MHz

Function Time Notes

LoG Filter 5.45 For 2 images

Recti�cation 20.04 Shift and rotate image

Dispairty Generation 33.47 SA 24, RA 15, 128�128 pixels

Flow Generation 16.30 SA 16, RA 8, 576 pt

Calc. 3D Depth Flow 0.53

(unit:msec): SA:Search Area, RA:Reference Area.

5 �#!�

EôJñòÿ�ñt�£ÓƼ¿��sòÿ�&-�@��ö���t�����£t����tmòÿ�&-�m��W�t�¦cï�£���å|�&-�ý¡ÃÓw¦lÕ�s�¤¦�|�<ì��&-��t�¦�¤���tJI5����s&-�ý¡ÃÓw�ö�|�ǽԳÌÑ?��~�¦lÕ��t��s3§�ØtÓƼ¿¦�|�s�G���2�[$�£òÿ���£ÓƼ¿�/¢Øt¦�|slÕ��5����H¦.��t

:8E41) \aIM, qB[@, mkZ. gl/>_%.eT+>_SDf(&+Y^/Jp$'>_<934+8;=6=0(571 2:=.bk<934ECECN, Vol. 12, No. 7, pp. 1029{1037, 1994.

2) UVdQ, WLR?. >_SDf/G,-!)_]hA/c!iKFH*"#.Oon`<934+XKjP. bk<934ECECN,Vol. 11, No. 6, pp. 856{867, 1993.

3) Oussama Khaib. Real-time obstacle avoidance for manipulatorsand mobile robots. International Journal of Robotics Research,Vol. 2, No. 1, pp. 57{72, 1986.

4) Y.Kitamura, T.Tanaka, F.Kishino, and M.Yachida. 3-d pathplanning in a dynamic environment using an octree and an ar-ti�cial potential �eld. In Proc. of the Int. Conf. on IntelligentRobots and Systems (IROS-95), pp. 474{481, 1995.

5) O. Faugeras, B. Hots, H. Mathieu, T. Vi�eville, Z. Zhang, P. Fua,E. Th�eron, L. Moll, G. Berry, J. Vuillemin, P. Bertin, andC. Proy. Real Time Correlation-Based Stereo: Algorithm, Im-plementations and Applications. Technical Report N�2013, IN-RIA, 1993.

6) R. Bolles and J. Wood�ll. Spatiotemporal Consistency Checkingof Passive Renge Data. In T. Kanade and R. Paul, editors,Robotics Research: The Sixth International Symposium, pp.165{183. International Foundation for Robotics Research, 1993.

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