Error-Aware Policy Learning: Zero-Shot Generalization in Partially Observable Dynamic Environments

Simulation provides a safe and efficient way to generate useful data for learning complex robotic tasks. However, matching simulation and real-world dynamics can be quite challenging, especially for systems that have a large number of unobserved or unmeasurable parameters, which may lie in the robot...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	arXiv.org 2021-03
Hauptverfasser:	Kumar, Visak, Ha, Sehoon, Liu, C Karen
Format:	Artikel
Sprache:	eng
Schlagworte:	Biomechanics Control tasks Errors Learning Reagents Robot dynamics Task complexity Walking
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!