A study on fingertip designs and their influences on performing stable prehension for robot hands

Keung Or, Shu Morikuni, Shun Ogasa, Satoshi Funabashi, Alexander Schmitz, Shigeki Sugano

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    This research aims to clarify and analyze potential factors in fingertip designs and conditions which may affect prehension performances in addition to the control strategy. In this paper, four factors of fingertip designs and conditions are considered: hardness, thickness of the skin, shape and the surface friction condition of the fingertip. Six fingertips were made in order to compare these factors and their influences on grasp stability under different conditions (high and low workload). An evaluation experiment was conducted in order to investigate how the proposed properties affect the grasping performance under different workloads. Results show an unexpected effectiveness of the soft skin grasping performance compared to less deformable materials, even with reduced friction; also the orientation of the fingertips significantly affects the grasping performance in the case of anthropomorphic fingertips. These results can be useful for designing a new robot hand and a control strategy, which can potentially lead to a better stability and efficient performance.

    Original languageEnglish
    Title of host publicationHumanoids 2016 - IEEE-RAS International Conference on Humanoid Robots
    PublisherIEEE Computer Society
    Pages772-777
    Number of pages6
    ISBN (Electronic)9781509047185
    DOIs
    Publication statusPublished - 2016 Dec 30
    Event16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016 - Cancun, Mexico
    Duration: 2016 Nov 152016 Nov 17

    Other

    Other16th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2016
    CountryMexico
    CityCancun
    Period16/11/1516/11/17

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Hardware and Architecture
    • Human-Computer Interaction
    • Electrical and Electronic Engineering

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