RLOC: Terrain-Aware Legged Locomotion Using Reinforcement Learning and Optimal Control

We present a unified model-based and data-driven approach for quadrupedal planning and control to achieve dynamic locomotion over uneven terrain. We utilize on-board proprioceptive and exteroceptive feedback to map sensory information and desired base velocity commands into footstep plans using a re...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE transactions on robotics Ročník 38; číslo 5; s. 2908 - 2927
Hlavní autori:	Gangapurwala, Siddhant, Geisert, Mathieu, Orsolino, Romeo, Fallon, Maurice, Havoutis, Ioannis
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.10.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	AI-based methods Computational modeling deep learning in robotics and automation Learning Legged locomotion legged robots Locomotion Optimal control Perturbation Physical properties Planning Policies Quadrupedal robots Robots robust/adaptive control of robotic systems Terrain Tracking Tracking control Training
ISSN:	1552-3098, 1941-0468
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!