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Learning adaptive manipulation of objects with revolute joint: A case
  study on varied cabinet doors opening

Learning adaptive manipulation of objects with revolute joint: A case study on varied cabinet doors opening

28 April 2023
Hongxiang Yu
Dashun Guo
Zhongxiang Zhou
Yue Wang
R. Xiong
ArXivPDFHTML

Papers citing "Learning adaptive manipulation of objects with revolute joint: A case study on varied cabinet doors opening"

3 / 3 papers shown
Title
Proximal Policy Optimization Algorithms
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
499
19,065
0
20 Jul 2017
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation
Data-efficient Deep Reinforcement Learning for Dexterous Manipulation
I. Popov
N. Heess
Timothy Lillicrap
Roland Hafner
Gabriel Barth-Maron
Matej Vecerík
Thomas Lampe
Yuval Tassa
Tom Erez
Martin Riedmiller
OffRL
71
264
0
10 Apr 2017
Domain Randomization for Transferring Deep Neural Networks from
  Simulation to the Real World
Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World
Joshua Tobin
Rachel Fong
Alex Ray
Jonas Schneider
Wojciech Zaremba
Pieter Abbeel
253
2,966
0
20 Mar 2017
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