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Autonomous Robots
Erschienen in: Autonomous Robots 1/2015

01.01.2015

Representing the robot’s workspace through constrained manipulability analysis

verfasst von: Nikolaus Vahrenkamp, Tamim Asfour

Erschienen in: Autonomous Robots | Ausgabe 1/2015

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Abstract

Quantifying the robot’s performance in terms of dexterity and maneuverability is essential for the analysis and design of novel robot mechanisms and for the selection of appropriate robot configurations in the context of grasping and manipulation. It can also be used for monitoring and evaluating the current robot state and support planning and decision making tasks, such as grasp selection or inverse kinematics (IK) computation. To this end, we propose an extension to the well-known Yoshikawa manipulability ellipsoid measure Yoshikawa (Int J Robotics Res 4(2):3–9, 1985), which incorporates constraining factors, such as joint limits or the self-distance between manipulator and other parts of the robot. Based on this measure we show how an extended capability representation of the robot’s workspace can be built in order to support online queries like grasp selection or inverse kinematics solving. In addition to single handed grasping tasks, we discuss how the approach can be extended to bimanual grasping tasks. The proposed approaches are evaluated in simulation and we show how the extended manipulability measure is used within the grasping and manipulation pipeline of the humanoid robot ARMAR-III.
Vorheriger Artikel Semi-task-dependent and uncertainty-driven world model maintenance
Nächster Artikel Decentralized dynamic task planning for heterogeneous robotic networks

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Fußnoten
1
All performance evaluations have been carried out on a single core 3GHz Linux PC.
 
2
The offline step of building the corresponding manipulability data took 6 h on a standard Linux PC.
 
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Metadaten
Titel
Representing the robot’s workspace through constrained manipulability analysis
verfasst von
Nikolaus Vahrenkamp
Tamim Asfour
Publikationsdatum
01.01.2015
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 1/2015
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-014-9394-z

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