Learning Robust and Agile Legged Locomotion Using Adversarial Motion Priors

Developing both robust and agile locomotion skills for legged robots is non-trivial. In this work, we present the first blind locomotion system capable of traversing challenging terrains robustly while moving rapidly over natural terrains. Our approach incorporates the Adversarial Motion Priors (AMP...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE robotics and automation letters Jg. 8; H. 8; S. 1 - 8
Hauptverfasser:	Wu, Jinze, Xin, Guiyang, Qi, Chenkun, Xue, Yufei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.08.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Behavioral sciences Coders Legged locomotion Legged Robots Locomotion Machine Learning for Robot Control Reinforcement Learning Robot dynamics Robot sensing systems Robots Robustness Sensors Task analysis Training
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!