Grasp Planning Using Low Dimensional Subspaces

  • Peter K. Allen
  • Matei Ciocarlie
  • Corey Goldfeder
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 95)

Abstract

Recent advances in neuroscience research have shown that posture variation of the human hand during grasping is dominated by movement in a configuration space of highly reduced dimensionality. In this chapter we explore how robot and artificial hands may take advantage of similar subspaces to reduce the complexity of dexterous grasping. We first describe our method for grasp synthesis using a low-dimensional posture subspace, and apply it to a set of hand models with different kinematics and numbers of degrees of freedom. We then discuss two applications of the method: online interactive grasp planning and data-driven grasp planning using a pre-computed database of stable grasps.

Keywords

Grasping Low-dimensional subspaces Robotic hands 

Notes

Acknowledgments

The authors would like to thank Hao Dang for his help in building the Columbia Grasp Database.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Peter K. Allen
    • 1
  • Matei Ciocarlie
    • 2
  • Corey Goldfeder
    • 3
  1. 1.Department of Computer ScienceColumbia UniversityNew YorkUSA
  2. 2.Willow Garage, Inc.Menlo ParkUSA
  3. 3.Google Inc.New YorkUSA

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