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    MagicHand: context-aware dexterous grasping using an anthropomorphic robotic hand

    Date
    2020-09-15
    Author
    Li, Hui
    Tan, Jindong
    He, Hongsheng
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    Citation
    H. Li, J. Tan and H. He, "MagicHand: Context-Aware Dexterous Grasping Using an Anthropomorphic Robotic Hand," 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 9895-9901
    Abstract
    Understanding of characteristics of objects such as fragility, rigidity, texture and dimensions facilitates and innovates robotic grasping. In this paper, we propose a context- aware anthropomorphic robotic hand (MagicHand) grasping system which is able to gather various information about its target object and generate grasping strategies based on the perceived information. In this work, NIR spectra of target objects are perceived to recognize materials on a molecular level and RGB-D images are collected to estimate dimensions of the objects. We selected six most used grasping poses and our system is able to decide the most suitable grasp strategies based on the characteristics of an object. Through multiple experiments, the performance of the MagicHand system is demonstrated.
    Description
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    URI
    https://doi.org/10.1109/ICRA40945.2020.9196538
    https://soar.wichita.edu/handle/10057/19589
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