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Task-Oriented Grasp Planning Based on Disturbance Distribution

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Robotics Research

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 114))

Abstract

One difficulty of task-oriented grasp planning is task modeling. In this paper, a manipulation task was modeled by building a non-parametric statistical distribution model from disturbance data captured during demonstrations. This paper proposes a task-oriented grasp quality criterion based on distribution of task disturbance and uses the criterion to search for a grasp that covers the most significant part of the disturbance distribution. To reduce the computational complexity of the search in a high-dimensional robotic hand configuration space, as well as to avoid a correspondence problem, the candidate grasps are computed from a reduced configuration space that is confined by a set of given thumb placements and thumb directions. The proposed approach has been validated with a Barrett hand and a Shadow hand on several objects in simulation. The resulting grasps in the evaluation generated by our approach increase the coverage of frequently-occurring disturbance rather than the coverage of a large area with a scattered distribution.

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Authors and Affiliations

  1. University of South Florida, 4202 E. Fowler Ave., ENB118, Tampa, FL, 33620-5399, USA

    Yun Lin & Yu Sun

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  1. Yun Lin
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  2. Yu Sun
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Correspondence to Yu Sun .

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Editors and Affiliations

  1. Creative Informatics, The University of Tokyo, Tokyo, Japan

    Masayuki Inaba

  2. School of Electrical Engineering and Com, Queensland Univ of Technology, Brisbane, Queensland, Australia

    Peter Corke

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Lin, Y., Sun, Y. (2016). Task-Oriented Grasp Planning Based on Disturbance Distribution. In: Inaba, M., Corke, P. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 114. Springer, Cham. https://doi.org/10.1007/978-3-319-28872-7_33

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  • DOI: https://doi.org/10.1007/978-3-319-28872-7_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28870-3

  • Online ISBN: 978-3-319-28872-7

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