Show simple item record Geng, Tao Lee, Mark Hülse, Martin 2011-02-22T14:40:10Z 2011-02-22T14:40:10Z 2011-02
dc.identifier.citation Geng , T , Lee , M & Hülse , M 2011 , ' Transferring human grasping synergies to a robot ' Mechatronics , vol 21 , no. 1 , pp. 272-284 . DOI: 10.1016/j.mechatronics.2010.11.003 en
dc.identifier.other PURE: 157909
dc.identifier.other PURE UUID: bdca4156-c18e-4bca-8dd8-669f1ad5e325
dc.identifier.other dspace: 2160/6135
dc.identifier.other DSpace_20121128.csv: row: 3951
dc.identifier.other Scopus: 79551505261
dc.description Geng, T., Lee, M., Huelse, M. (2011). Transferring human grasping synergies to a robot. Mechatronics, 21 (1), 272-284. Sponsorship: EC en
dc.description.abstract In this paper, a system for transferring human grasping skills to a robot is presented. In order to reduce the dimensionality of the grasp postures, we extracted three synergies from data on human grasping experiments and trained a neural network with the features of the objects and the coefficients of the synergies. Then, the trained neural network was employed to control robot grasping via an individually optimized mapping between the human hand and the robot hand. As force control was unavailable on our robot hand, we designed a simple strategy for the robot to grasp and hold the objects by exploiting tactile feedback at the fingers. Experimental results demonstrated that the system can generalize the transferred skills to grasp new objects. en
dc.format.extent 13 en
dc.language.iso eng
dc.relation.ispartof Mechatronics en
dc.rights en
dc.title Transferring human grasping synergies to a robot en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Intelligent Robotics Group en
dc.description.status Peer reviewed en

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