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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bullock, I.M. Feix, T. Dollar, A.M. |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Mech. Eng. & Mater. Sci., Yale Univ., New Haven, CT, USA (Bullock, I.M.; Feix, T.; Dollar, A.M.) |
| Abstract | Robotic and prosthetic hand designers are challenged to replicate as much functionality of the human hand as possible, while minimizing cost and any unnecessary complexity. Selecting which aspects of human hand function to emulate can be difficult, especially when little data is available on unstructured human manipulation behavior. The present work analyzes 19 hours of video with over 9000 grasp instances from two housekeepers and two machinists to find small sets of versatile human grasps. A novel grasp span metric is used to evaluate sets of grasps and pick an optimal grasp set which can effectively handle as many different objects as possible. The results show medium wrap and lateral pinch are both important, versatile grasps for basic object handling. The results suggest that three-fingertip precision grasps such as thumb-2 finger, tripod, or lateral tripod can be used to handle dexterous manipulation of a wide range of objects. The recommended grasp sets can help aid difficult design decisions for robotic and prosthetic hands, as well as suggesting important human hand functionality to restore during hand surgery or rehabilitate in an impaired hand. |
| Starting Page | 1068 |
| Ending Page | 1075 |
| File Size | 1576394 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781467356411 |
| ISSN | 10504729 |
| e-ISBN | 9781467356435 |
| DOI | 10.1109/ICRA.2013.6630705 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-05-06 |
| Publisher Place | Germany |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Taxonomy Grasping Robots Measurement Thumb Prosthetic hand |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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