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Erschienen in: Intelligent Service Robotics 2/2017

28.01.2017 | Original Research Paper

Design of an anthropomorphic dual-arm robot with biologically inspired 8-DOF arms

verfasst von: Dong-Hyuk Lee, Hyeonjun Park, Jae-Han Park, Moon-Hong Baeg, Ji-Hun Bae

Erschienen in: Intelligent Service Robotics | Ausgabe 2/2017

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Abstract

From the perspective of kinematics, dual-arm manipulation in robots differs from single-arm manipulation in that it requires high dexterity in a specific region of the manipulator’s workspace. This feature has motivated research on the specialized design of manipulators for dual-arm robots. These recently introduced robots often utilize a shoulder structure with a tilted angle of some magnitude. The tilted shoulder yields better kinematic performance for dual-arm manipulation, such as a wider common workspace for each arm. However, this method tends to reduce total workspace volume, which results in lower kinematic performance for single-arm tasks in the outer region of the workspace. To overcome this trade-off, the authors of this study propose a design for a dual-arm robot with a biologically inspired four degree-of-freedom shoulder mechanism. This study analyzes the kinematic performance of the proposed design and compares it with that of a conventional dual-arm robot from the perspective of workspace and single-/dual-arm manipulability. The comparative analysis revealed that the proposed structure can significantly enhance single- and dual-arm kinematic performance in comparison with conventional dual-arm structures. This superior kinematic performance was verified through experiments, which showed that the proposed method required shorter settling time and trajectory-following performance than the conventional dual-arm robot.

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Metadaten
Titel
Design of an anthropomorphic dual-arm robot with biologically inspired 8-DOF arms
verfasst von
Dong-Hyuk Lee
Hyeonjun Park
Jae-Han Park
Moon-Hong Baeg
Ji-Hun Bae
Publikationsdatum
28.01.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Intelligent Service Robotics / Ausgabe 2/2017
Print ISSN: 1861-2776
Elektronische ISSN: 1861-2784
DOI
https://doi.org/10.1007/s11370-017-0215-z

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