
Open access
Date
2018-03Type
- Journal Article
ETH Bibliography
no
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Abstract
This work presents a soft hand capable of robustly grasping and identifying objects based on internal state measurements along with a combined system which autonomously performs grasps. A highly compliant soft hand allows for intrinsic robustness to grasping uncertainties; the addition of internal sensing allows the configuration of the hand and object to be detected. The finger module includes resistive force sensors on the fingertips for contact detection and resistive bend sensors for measuring the curvature profile of the finger. The curvature sensors can be used to estimate the contact geometry and thus to distinguish between a set of grasped objects. With one data point from each finger, the object grasped by the hand can be identified. A clustering algorithm to find the correspondence for each grasped object is presented for both enveloping grasps and pinch grasps. A closed loop system uses a camera to detect approximate object locations. Compliance in the soft hand handles that uncertainty in addition to geometric uncertainty in the shape of the object. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000425035Publication status
publishedExternal links
Journal / series
Autonomous RobotsVolume
Pages / Article No.
Publisher
SpringerSubject
Soft Robotics; Soft Gripper; Proprioceptive soft robotic hand; Proprioceptive sensing; Online object identification; Learning new objects; Autonomously GraspingOrganisational unit
09689 - Katzschmann, Robert / Katzschmann, Robert
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ETH Bibliography
no
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