Advertisement

Vision-Based Grasping Points Determination by Multifingered Hands

  • Madjid Boudaba
  • Alicia Casals
  • Dirk Osswald
  • Heinz Woern
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 25)

Summary

This paper discusses some issues for generating points of contact on object grasping by multifingered robot hands. To address these issues, we present a general algorithm based on computer vision techniques for determining grasping points through a sequence of processes: (1) object’s visual features, we apply some algorithms for extracting vertices, edges, object’s contours, (3) modeling the point of contact by a bounded polytope, (3) based on these features, the developed algorithm starts by analysing the object’s contour to generate a set of contact points that guarantee the force-closure grasps condition. Finally, we briefly describe some experiments on a humanoid robot with a stereo camera head and an anthropomorphic robot hand within the “Center of Excellence on Humanoid Robots: Learning and co-operating Systems” at the University of Karlsruhe and the Forschungszentrum Karlsruhe.

Keywords

Vision system Points of contacts Force-closure Grasping Linear programmimg implementation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Shimoga K. B, (1996) Robot grasp synthesis algorithms: A survey, Int. Journal of Robotics Research, 15(3):230–266Google Scholar
  2. 2.
    Murray R. M, Li Z, and Sastry S. S (1994) A Mathematical Introduction to Robotic Manipulation, CRC Press, Boca Raton, New YorkzbMATHGoogle Scholar
  3. 3.
    Mishra B, Schwartz J. T, Sharir M, (1987) On the existence and synthesis of multifinger positive grips, Algorithmica (3)Google Scholar
  4. 4.
    Martin B, Canny J, (1994) Easily Computable Optimum Grasps in 2-D and 3-D 2, IEEE Int. Conf. on Robotics and Automation, 739–747, San Diego, CAGoogle Scholar
  5. 5.
    Kerr J. and Roth B, (1986) Analysis of multifingered hands, Int. J. of Robotics Research, 4(4):3–17Google Scholar
  6. 6.
    Nguyen V. D, (1988) Constructing force-closure grasps, International Journal of Robotics Research, 7(3):3–16Google Scholar
  7. 7.
    Ferrari C, Canny J. F, (1992) Planning Optimal Grasps, Int. Conf. on Robotics and Automation, 2290–2295Google Scholar
  8. 8.
    Ponce J, Sullivan S, Boissonnat J. D, Merlet J. P, 8(1993) On characterizing and computing three-and four-finger force-closure grasps of polyhedral objects,” International Conference in Robotics and Automation.Google Scholar
  9. 9.
    Boudaba M, Casals A, (2000) Robot Grasps: A survey and development of a grasping procedure, Technical report, ESAII-RR-00-15, Dept. ESAII, Technical University of Catalonia, Barcelona, SpainGoogle Scholar
  10. 10.
    Boudaba M, Casals A, (2005) Polyhedral Convex Cones for Computing Feasible Grasping Regions from Vision, 6th IEEE CIRA Symposium, Espoo, FinlandGoogle Scholar
  11. 11.
    Brost R. C, (1991) Analysis and planning of planar manipulation tasks, Ph.D. thesis. Carnegie Mellon University. School of Computer ScienceGoogle Scholar
  12. 12.
    Liu Y. H, (1998) Computing n-finger force-closure grasps on polygonal objects, Proc. IEEE Int. Conf. on Robotics and Automation, 2734–2739Google Scholar
  13. 13.
    Hirai S, Asada H, (1993) Kinematics and Statics of Manupulation using the Theory of Polyhedral Convex cones, Int. J. of Robotics Research, 12(5):434–447.Google Scholar
  14. 14.
    Ishii I, Nakabo Y, Ishikawa M, (1996) Target traking algorithm for 1ms visual feedback system using massively parallel processing vision, Int. Conf. on Robotics and Automation, 2309–2314.Google Scholar
  15. 15.
    Maekawa H, K. Tanie H. K, Komoriya K, (1995) Tactile sensor based manipulation of an unknown object by a multifingered hand with rolling contact, IEEE ICRA, 743–750Google Scholar
  16. 16.
    Yoshimi B, Allen P, (1998) Visual control of grasping,” In D. Kriegman, G. Hagar, and S. Morse, Editors, The Confluence of Vision and Control, 195–209, Springer-Verlag.Google Scholar
  17. 17.
    Namiki A, Nakabo Y, Ishii I, Ishikawa M, (1999) High speed grasping using visual and force feedback, Int. Conf. on Robotics and Automation, 3195–3200.Google Scholar
  18. 18.
    de Berg M, Van Kreveld M, Overmars M, Schwarzkopf O, (1997) Computational Geometry: Algorithms and Applications, 2nd ed., Springer-Verlag.Google Scholar
  19. 19.
    Goldman A. J, Tucker A. W, (1956) Polyhedral Convex Cones, in Linear Inequalities and Related Systems, Annals of Math. Studies, Princeton, 38:19–40Google Scholar
  20. 20.
    Kvasnica M, Grieder P, Boatc M, Christophersen F. J, (2004) MPT2.0, http://control.ee.eth.z/mpt. User’s Guide, Swiss Federal Institute.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Madjid Boudaba
    • 1
  • Alicia Casals
    • 2
  • Dirk Osswald
    • 3
  • Heinz Woern
    • 3
  1. 1.TES Electronic Solutions GmbHStuttgartGermany
  2. 2.Automatic Control and Computer Engineering Dpt.(ESAII)Technical University of CataloniaBarcelonaSpain
  3. 3.Institute of Process Control and Robotics (IPR)University of KarlsruheKarlsruheGermany

Personalised recommendations