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Learning and Execution of Object Manipulation Tasks on Humanoid Robots

Equipping robots with complex capabilities still requires a great amount of effort. In this work, a novel approach is proposed to understand, to represent and to execute object manipulation tasks learned from observation by combining methods of data analysis, graphical modeling and artificial intell...

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Bibliografische gegevens
Hoofdauteur: Wächter, Mirko (auth)
Formaat: Elektronisch Hoofdstuk
Taal:Engels
Gepubliceerd in: KIT Scientific Publishing 2018
Reeks:Karlsruhe Series on Humanoid Robotics
Onderwerpen:
Autonomous systems
Graphical programming
Humanoide Robotik
Programming by demonstration
Autonome Systeme
Robotik
Programmieren durch Vormachen
Robotics
Humanoid robotics
Graphische Programmierung
Online toegang:DOAB: download the publication
DOAB: description of the publication
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Omschrijving
Samenvatting:Equipping robots with complex capabilities still requires a great amount of effort. In this work, a novel approach is proposed to understand, to represent and to execute object manipulation tasks learned from observation by combining methods of data analysis, graphical modeling and artificial intelligence. Employing this approach enables robots to reason about how to solve tasks in dynamic environments and to adapt to unseen situations.
Fysieke beschrijving:1 electronic resource (X, 236 p. p.)
ISBN:KSP/1000078313
9783731507499
Toegang:Open Access

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