Human-Robot Body Experience: An Artificial Intelligence Perspective
Autor(en):
Zusammenfassung
Human body experience is remarkably flexible, which enables us to integrate passive tools as well as intelligent robotic devices into our body representation. Accordingly, it can serve as a role model to make (assistive) robots interact seamlessly with their users or to provide (humanoid) robots with a human-like self-perception and behavior generation. This article discusses the potential of understanding human body experience and applying it to robotics. Particular focus is set on how to use artificial intelligence techniques and create intelligent artificial agents from insights about human body experience. The discussion is based on a summary of the author’s habilitation thesis and combines theoretical and experimental perspectives from psychology, cognitive science and neuroscience as well as computer science, engineering, and artificial intelligence. From this, it derives directions for future developments towards creating artificial body intelligence with human-like capabilities.
- Vollständige Referenz
- BibTeX
Beckerle, P.,
(2022).
Human-Robot Body Experience: An Artificial Intelligence Perspective.
KI - Künstliche Intelligenz: Vol. 36, No. 0.
Springer.
(S. 267-270).
DOI: 10.1007/s13218-022-00779-1
@article{mci/Beckerle2022,
author = {Beckerle, Philipp},
title = {Human-Robot Body Experience: An Artificial Intelligence Perspective},
journal = {KI - Künstliche Intelligenz},
volume = {36},
number = {0},
year = {2022},
,
pages = { 267-270 } ,
doi = { 10.1007/s13218-022-00779-1 }
}
author = {Beckerle, Philipp},
title = {Human-Robot Body Experience: An Artificial Intelligence Perspective},
journal = {KI - Künstliche Intelligenz},
volume = {36},
number = {0},
year = {2022},
,
pages = { 267-270 } ,
doi = { 10.1007/s13218-022-00779-1 }
}
Sollte hier kein Volltext (PDF) verlinkt sein, dann kann es sein, dass dieser aus verschiedenen Gruenden (z.B. Lizenzen oder Copyright) nur in einer anderen Digital Library verfuegbar ist. Versuchen Sie in diesem Fall einen Zugriff ueber die verlinkte DOI: 10.1007/s13218-022-00779-1
Haben Sie fehlerhafte Angaben entdeckt? Sagen Sie uns Bescheid: Feedback abschicken
Mehr Information
ISSN: 1610-1987
Datum: 2022
Typ: Text/Journal Article

