Grasp recognition by time-clustering, fuzzy modeling, and Hidden Markov Models (HMM) - a comparative study

@article{Palm2008GraspRB,
  title={Grasp recognition by time-clustering, fuzzy modeling, and Hidden Markov Models (HMM) - a comparative study},
  author={Rainer Palm and Boyko Iliev},
  journal={2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={599-605}
}
This paper deals with three different methods for grasp recognition for a human hand. Grasp recognition is a major part of the approach for programming-by-demonstration (PbD) for five-fingered robotic hands. A human operator instructs the robot to perform different grasps wearing a data glove. For a number of human grasps, the finger joint angle trajectories are recorded and modeled by fuzzy clustering and Takagi-Sugeno modeling. This leads to grasp models using the time as input parameter and… CONTINUE READING
6 Citations
14 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 14 references

Generation of control sequences for a fuzzy gain scheduler

  • R. Palm, Ch. Stutz
  • International Journal of Fuzzy Systems,
  • 2003
1 Excerpt

Task recognition and human-machine coordination through the use of an instrument-glove

  • H. H. Asada, J. R. Fortier
  • Progress report No
  • 2000
3 Excerpts

Similar Papers

Loading similar papers…