An SVM learning approach to robotic grasping

@article{Pelossof2004AnSL,
  title={An SVM learning approach to robotic grasping},
  author={Raphael Pelossof and Andrew T. Miller and Peter K. Allen and Tony Jebara},
  journal={IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004},
  year={2004},
  volume={4},
  pages={3512-3518 Vol.4}
}
Finding appropriate stable grasps for a hand (either robotic or human) on an arbitrary object has proved to be a challenging and difficult problem. The space of grasping parameters coupled with the degrees-of-freedom and geometry of the object to be grasped creates a high-dimensional, non-smooth manifold. Traditional search methods applied to this manifold are typically not powerful enough to find appropriate stable grasping solutions, let alone optimal grasps. We address this issue in this… CONTINUE READING
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