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Alexander Bannat
Researcher at Technische Universität München
Publications - 28
Citations - 477
Alexander Bannat is an academic researcher from Technische Universität München. The author has contributed to research in topics: Human–robot interaction & Gesture. The author has an hindex of 9, co-authored 28 publications receiving 447 citations. Previous affiliations of Alexander Bannat include Information Technology Institute & Institute for Infocomm Research Singapore.
Papers
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Journal ArticleDOI
Artificial Cognition in Production Systems
Alexander Bannat,Thibault Bautze,Michael Beetz,Jürgen Blume,Klaus Diepold,Christoph Ertelt,Florian Geiger,Thomas Gmeiner,T Gyger,Alois Knoll,C. Lau,Claus Lenz,M. Ostgathe,Gunther Reinhart,W Roesel,Thomas Ruehr,Anna Schuboe,Kristina Shea,Ingo Stork genannt Wersborg,Sonja Stork,W Tekouo,Frank Wallhoff,M. Wiesbeck,Michael F. Zaeh +23 more
TL;DR: The general principles of autonomy and the proposed concepts, methods and technologies to realize cognitive planning, cognitive control and cognitive operation of production systems to realize fully autonomous components of an production system as well as autonomous parts and products are presented.
Proceedings ArticleDOI
Joint-action for humans and industrial robots for assembly tasks
Claus Lenz,Suraj Nair,Markus Rickert,Alois Knoll,Wolfgang Rösel,Jürgen Gast,Alexander Bannat,Frank Wallhoff +7 more
TL;DR: A concept of a smart working environment designed to allow true joint-actions of humans and industrial robots, which anticipates human behavior, based on knowledge databases and decision processes, ensuring an effective collaboration between the human and robot.
Book ChapterDOI
A Multimodal Human-Robot-Interaction Scenario: Working Together with an Industrial Robot
TL;DR: A novel approach for multimodal interactions between humans and industrial robots in a factory, where a human worker is supported by a robot to accomplish a given hybrid assembly scenario, that covers manual and automated assembly steps.
Journal ArticleDOI
A skill-based approach towards hybrid assembly
TL;DR: A hybrid assembly station is presented, in which an industrial robot can learn new tasks from worker instructions, and the functionality is demonstrated within an experimental cell in a real-world production scenario.
Towards Optimal Worker Assistance -- A Framework for Adaptive Selection and Presentation of Assembly Instructions
Alexander Bannat,F. Wallhoff,G. Rigoll,Florian Friesdorf,Heiner Bubb,S. Stork,H. Mueller,A. Schuboe,M. Wiesbeck,Michael F. Zaeh +9 more
TL;DR: In this article, an adaptive and cognitive system for worker guidance is proposed to provide the worker with assistive information, adapted to the situation and cognitive state of the worker, based on an adaptive process model and findings from experiments about human cognition.