INFORMATION-BASED INVERSE KINEMATCS MODELING FOR ANIMATION AND ROBOTICS

Mikyung Kim, Mahmoud Tarokh

Abstract

The paper proposes a novel method for extremely fast inverse kinematics computation suitable for animation of anthropomorphic limbs, and fast moving lightweight manipulators. In the information intensive preprocessing phase, the workspace of the robot is decomposed into small cells, and joint angle vectors (configurations) and end-effector position/ orientation (posture) data sets are generated randomly in each cell using the forward kinematics. Due to the existence of multiple solutions for a desired posture, the generated configurations form clusters in the joint space which are classified. After the classification, the data belonging to each solution is used to determine the parameters of simple polynomial or neural network models that closely approximates the inverse kinematics within a cell. These parameters are stored in a lookup file. During the online phase, given the desired posture, the index of the appropriate cell is found, the model parameters are retrieved, and the joint angles are computed. The advantages of the proposed method over the existing approaches are discussed in the paper. In particular, the method is complete (provides all solutions), and is extremely fast. Statistical analyses for an industrial manipulator and an anthropomorphic arm are provided using both polynomial and neural network inverse kinematics models, which demonstrate the performance of the proposed method.

References

  1. Chapelle, F., and P. Bidaud, 2001. A Closed form for inverse kinematics approximation of general 6R manipulators using genetic programming” Proc. IEEE Int. Conf. Robotics and Automation, pp. 3364-3369.
  2. Chiacchio, P., S. Chiaverini, L. Sciavicco and B. Sciliano, 1991.Closed-loop inverse kiematic schemes for constrained redundant manipulators with task space augmentation and task priority strategy,” Int. J. Robotics Research, pp. 410-425, vol. 10, no. 4.
  3. Chiaverini,S., B. Sciliano and O. Egeland, 1994. Review of dampedleast squares inverse kinematics with experiments on an industrial robot manipulator,” IEEE Trans. Control Systems Technology, pp. 123-134, vol. 2, no. 2, 1994.
  4. De Lope, R. Gonzalez-Careaga, and T. Zarraonandia, 2003. Inverse kinematics of humanoid robots using artificial neural networks,” EUROCAST 2003, Proc. Int. Workshop on Computer Aided System Theory, p.216-218.
  5. Dermatas E., Nearchou A., and Aspragathos N.,1996.
  6. Error - Backpropagation Solution to the Inverse Kinematic Problem of Redundant Manipulators," Journal of Robotics and Computer Integrated Manufacturing, pp. 303-310, vol. 12, no. 4.
  7. Khwaja,A., M. O. Rahman and M.G. Wagner, 1998.
  8. Inverse Kinematics of Arbitrary Robotic Manipulators Using Genetic Algorithms, in J. Lenarcic and M. L. Justy (editors), Advances in Robot Kinematics: Analysis and Control, pp. 375--382, Kluwer Academic Publishers.
  9. Klein, C.A. and C. H. Huang, 1983. Review of pseudoinverse control for use with kinematically redundant manipulators,” IEEE Trans. Systems, Man, and Cybernetics, vol. SMC-13, no. 3, pp. 245-250.
  10. Lloyed, J.E., and V. Hayward, 2001. Singularity robust trajectory generation,” Int. J. Robotics Research, pp. 38- 56, vol. 20, no. 1.
  11. Manchoa, C. and J.F. Canny, 1994. Efficient inverse Kinematics of general 6R maipulators,” IEEE Trans. Robotics and Automation, pp. 648-657, vol 10, no. 5.
  12. Nearchou, A.C., 1998. Solving the inverse kinematics problem of redundant robots operationg in complex environments via a modified genetic algorithm”, J. Mech. Mach. Theory, vol. 33, no. 3, pp. 273-292.
  13. Vetterling, 1988. Numerical Recipe in C, Cambridge University Press, Cambridge, U.K.
  14. Seraji, H., M.K. Long and T.S. Lee, 1993. Motion control of 7- DOF arms: the configuration control approach,” IEEE Trans. Robotics and Automation, pp. 125-139, vo. 9, no. 2.
  15. Tarokh, M. and K. Keerthi, 2005. Inverse Kinematics solutions of Anthropomorphic Limbs by Decomposition and Fuzzy Classification, in Proc. Int. Conf. on Artificial Intelligence, Las Vagas.
  16. Tolani, D, A. Goswami and N. Badler, 2000. Real-time inverse kinematics techniques for anthropomorphic limbs,” Graphic Models, pp. 353-388, vol. 62.
  17. Uicker, J. J, J. Denavit and R.S. Hartenberg, 1984. An iterative method for the displacement analysis of spatial mechanisms, J. Applied Mechanics, ASME, pp. 309-314.
  18. Whitney, D.E., 1972. The mathematics of coordinated control prosthetic arm and manipulators,” Trans. ASME J. Dynamic Systems, Measurement and Control , pp. 303-309, vol. 94.
  19. Zhao, X. and N. Badler, 1994. Inverse kinematic positioning using nonlinear programming for highly articulated figures,” Trans. Computer Graphics, pp. 313-336, vol. 13, no. 4.
Download


Paper Citation


in Harvard Style

Kim M. and Tarokh M. (2005). INFORMATION-BASED INVERSE KINEMATCS MODELING FOR ANIMATION AND ROBOTICS . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 972-8865-30-9, pages 76-84. DOI: 10.5220/0001164600760084


in Bibtex Style

@conference{icinco05,
author={Mikyung Kim and Mahmoud Tarokh},
title={INFORMATION-BASED INVERSE KINEMATCS MODELING FOR ANIMATION AND ROBOTICS},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2005},
pages={76-84},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001164600760084},
isbn={972-8865-30-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - INFORMATION-BASED INVERSE KINEMATCS MODELING FOR ANIMATION AND ROBOTICS
SN - 972-8865-30-9
AU - Kim M.
AU - Tarokh M.
PY - 2005
SP - 76
EP - 84
DO - 10.5220/0001164600760084