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URN: urn:nbn:de:swb:90-477899

A Continuous Grasp Representation for the Imitation Learning of Grasps on Humanoid Robots

Do, Martin Minh Thong

Abstract:
Models and methods are presented which enable a humanoid robot to learn reusable, adaptive grasping skills. Mechanisms and principles in human grasp behavior are studied. The findings are used to develop a grasp representation capable of retaining specific motion characteristics and of adapting to different objects and tasks. Based on the representation a framework is proposed which enables the robot to observe human grasping, learn grasp representations, and infer executable grasping actions.


Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Jahr 2014
Sprache Englisch
Identifikator KITopen-ID: 1000047789
Verlag Karlsruhe
Abschlussart Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdaten 12.06.2014
Referent/Betreuer Prof. R. Dillmann
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