Inferring Versatile Behavior from Demonstrations by Matching Geometric Descriptors

Humans intuitively solve tasks in versatile ways, varying their behavior in terms of trajectory-based planning and for individual steps. Thus, they can easily generalize and adapt to new and changing environments. Current Imitation Learning algorithms often only consider unimodal expert demonstratio...

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Veröffentlicht in:	arXiv.org 2022-11
Hauptverfasser:	Freymuth, Niklas, Schreiber, Nicolas, Becker, Philipp, Taranovic, Aleksandar, Neumann, Gerhard
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Changing environments Configurations Human behavior Machine learning Matching Trajectory planning
Online-Zugang:	Volltext
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