Abstract

Development of Push-Recovery control system for humanoid robots using deep reinforcement learning

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Similar Papers

Paper Title
Journal
Date
Author
Deep Reinforcement Learning: A New Frontier in Computer Vision Research
Sejuti Rahman ... Sujan Sarker
-
Sejuti Rahman, et. al.Sejuti Rahman ... Sujan Sarker
01 Jan 2020
Sample effficient deep reinforcement learning for control
-
15 Dec 2019
Deep Interactive Reinforcement Learning for Path Following of Autonomous Underwater Vehicle
Qilei Zhang ... Qixin Sha
IEEE access : practical innovations, open solutions | VOL. 8
Qilei Zhang, et. al.Qilei Zhang ... Qixin Sha
01 Jan 2020
Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey
Lanyu Xu ... Simeng Zhu
Physics in Medicine and Biology | VOL. 67
Lanyu Xu, et. al.Lanyu Xu ... Simeng Zhu
11 Nov 2022
View more papers

More From: Ain Shams Engineering Journal

Paper Title
Journal
Date
Author
A stability improvement control strategy research for LLC resonant converter with single neuron PI-I double closed loop control
Zhangang Yang ... Qingyu Zhou
Ain Shams Engineering Journal | VOL. -
Zhangang Yang, et. al.Zhangang Yang ... Qingyu Zhou
01 Jul 2024
Editorial Board
-
Ain Shams Engineering Journal | VOL. 15
--
01 Jul 2024
Fault current limitation approaches for grid-following controlled DERs in microgrid environments
C García-Ceballos ... J Mora-Flórez
Ain Shams Engineering Journal | VOL. -
C García-Ceballos, et. al.C García-Ceballos ... J Mora-Flórez
01 Jun 2024
Study on properties of reinforced concrete structures in seismic regions
Ke Li
Ain Shams Engineering Journal | VOL. -
Ke LiKe Li
01 Jun 2024
View more papers