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arxiv: 1904.03754 · v3 · pith:YF56XAX3new · submitted 2019-04-07 · 💻 cs.RO · cs.CV

ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact

classification 💻 cs.RO cs.CV
keywords functionalcontactgraspobjectsynthesiscontactgrasphandsobjects
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Grasping and manipulating objects is an important human skill. Since most objects are designed to be manipulated by human hands, anthropomorphic hands can enable richer human-robot interaction. Desirable grasps are not only stable, but also functional: they enable post-grasp actions with the object. However, functional grasp synthesis for high degree-of-freedom anthropomorphic hands from object shape alone is challenging because of the large optimization space. We present ContactGrasp, a framework for functional grasp synthesis from object shape and contact on the object surface. Contact can be manually specified or obtained through demonstrations. Our contact representation is object-centric and allows functional grasp synthesis even for hand models different than the one used for demonstration. Using a dataset of contact demonstrations from humans grasping diverse household objects, we synthesize functional grasps for three hand models and two functional intents. The project webpage is https://contactdb.cc.gatech.edu/contactgrasp.html.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Towards Markerless Grasp Capture

    cs.CV 2019-07 unverdicted novelty 4.0

    The paper proposes a preliminary markerless grasp capture method from video that uses 2D hand pose estimation plus optimization to also model hand-object contact.