DOI QR코드

DOI QR Code

스테레오정합과 신경망을 이용한 3차원 잡기계획

3D Grasp Planning using Stereo Matching and Neural Network

  • 이현기 (경북대학교 기계공학과) ;
  • 배준영 (경북대학교 대학원 기계공학과) ;
  • 이상룡 (경북대학교 기계공학부)
  • 발행 : 2003.07.01

초록

This paper deals with the synthesis of the 3-dimensional grasp planning for unknown objects. Previous studies have many problems, which the estimation time for finding the grasping points is much long and the analysis used the not-perfect 3-dimensional modeling. To overcome these limitations in this paper new algorithm is proposed, which algorithm is achieved by two steps. First step is to find the whole 3-dimensional geometrical modeling for unknown objects by using stereo matching. Second step is to find the optimal grasping points for unknown objects by using the neural network trained by the result of optimization using genetic algorithm. The algorithm is verified by computer simulation, comparing the result between neural network and optimization.

키워드

참고문헌

  1. Nguyen, V.-D., 1988, 'Constructing force-closure grasps,' The International Journal of Robotics Research, 7(3) https://doi.org/10.1177/027836498800700301
  2. Hauck, A., Ruttinger, J., Sorg, M., and Farber, G, 1999, 'Visual Determination of 3D Grasping Points on Unknown Objects with a Binocular Camera System,' In Proceeding of the IEEE/RSJ International Conference on Intelligent robots and System, pp. 272-278 https://doi.org/10.1109/IROS.1999.813016
  3. Morales, A., Recattala, G, Pedro J. Sanz, and Angel P. del Pobil, 2001, 'Heuristic Vision-Based Computation of Planar Antipodal Grasps on Unknown Objects,' In Proceeding of the IEEE International Conference on Robotic & Automation, Seoul, Korea https://doi.org/10.1109/ROBOT.2001.932613
  4. Borst, Ch., Fischer, M., and Hirzinger, G, 1999, 'A Fast and Robust Grasp Planner for Arbitary 3D Objects,' In Proc. of IEEE International Conference on Robotics & Automation, Detroit, Michigan https://doi.org/10.1109/ROBOT.1999.770384
  5. Ferrari, C., and Canny, J., 1992, 'Planning Optimal Grasps,' In Proceeding of the IEEE International Conference on Robotics & Automation, pp. 2290-2295, Nice, France https://doi.org/10.1109/ROBOT.1992.219918
  6. Katada, Y., Svinin, M., Ohkura, K., and Ueda, K., 2001, 'Optimization of Stable Grasps by Evolutionary Programming,' In Proceeding of the 32nd ISR
  7. Hyun-Ki Lee, Myun-Hee Kim and Sang-Ryong Lee, 2002, 'Optimization of 3D Grasping Points with Whole 3D Modeling for Unknown Object,' In Proc. Of the 2nd China-Korea Joint Workshop on Robotics, Shenyang, China
  8. Fusiello, A., Trucco, E., and Verri, A., 2000, 'A Compact Algorithm for Rectification of Stereo Pairs,' Machine Vision and Applications, 12(1): 16-22 https://doi.org/10.1007/s001380050003
  9. Laszlo, J., 'Computational Geometry and computer graphics in C++,' Prentice Hall Press
  10. Hyun-Hyup Lee and Kyung-Il Mun, 'Fuzzy-Neuro by using a MATLAB,' Ajin Press
  11. Maybank, S. J., and Faugeras, O., 1992, 'A Theory of Self-Calibration of a Moving Camera,' International Journal of computer Vision, 8(2): 123-151 https://doi.org/10.1007/BF00127171
  12. Zhang, Z., 1998, 'A Flexible New Technique for Camera Calibration,' Technical Report MSRTR-98-71, Microsoft Research
  13. Zhang, Z., 1999, 'Flexible Camera Calibration by Viewing a Plane from Unknown Orientations,' In Proc. 7th International Conference on Computer Vision, Kerkyra, Greece, pp. 666-673 https://doi.org/10.1109/ICCV.1999.791289
  14. HeikkiHi, J., and Silveri, 0., 1997, 'A Four-step Camera Calibration Procedure with Implicit Image Correction,' In IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVRP'97), San Juan, Puerto Rico, pp. 1106-1112 https://doi.org/10.1109/CVPR.1997.609468
  15. Kim, G B., Chung, S. C., 2001, 'A Stereo Matching Algorithm with Projective Distortion of Variable Windows,' Transactions of KSME, A, Vol. 25, No.3, pp.461-469
  16. Park, K., 1999, '3D Object Recognition and Accurate Pose Calculation Using a Neural Network,' Transactions of KSME, A, Vol. 23, No. 11, pp. 1929-1939