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Finger-gaiting manipulation is an important skill to achieve large-angle in-hand re-orientation of objects.
“Reorienting Objects with a Robot Hand Using Grasp Gaits”
Susanna Leveroni and Kenneth Salisbury · 1996
Earlier work this paper cites.
“Regrasps by a multifingered hand based on primitives”
T Omata and M Farooqi · 1996
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“Precision object manipulation with a multifingered robot hand”
P Michelman · 1998
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“Dextrous manipulation by rolling and finger gaiting”
L Han and J Trinkle · 1998
Earlier work this paper cites.
“An overview of dexterous manipulation”
A Okamura, N Smaby and M Cutkosky · 2000
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“On the sample complexity of reinforcement learning”
Sham Kakade · 2003
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“The linear programming approach to approximate dynamic programming”
D de Farias and B Van · 2003
Earlier work this paper cites.
“Manipulation gaits: sequences of grasp control tasks”
R Platt, A Fagg and R Grupen · 2004
Earlier work this paper cites.
“Dexterous manipulation planning using probabilistic roadmaps in continuous grasp subspaces”
Jean-Philippe Saut, Anis Sahbani, Sahar El-Khoury and Veronique Perdereau · 2007
Earlier work this paper cites.
“Synthesis and stabilization of complex behaviors through online trajectory optimization”
Y Tassa, T Erez and E Todorov · 2012
Cited alongside, same era.
“MuJoCo: A physics engine for model-based control”
Emanuel Todorov, Tom Erez and Yuval Tassa · 2012
Cited alongside, same era.
“Learning robot in-hand manipulation with tactile features”
Herke van Hoof, Tucker Hermans, Gerhard Neumann and Jan Peters · 2015
Cited alongside, same era.
“Proximal Policy Optimization Algorithms”, 2017
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford and Oleg Klimov · 2017
Cited alongside, same era.
“Real-Time Finger Gaits Planning for Dexterous Manipulation**This project was supported by FANUC Corporation” 20th IFAC World Congress
Yongxiang Fan, Wei Gao, Wenjie Chen and Masayoshi Tomizuka · 2017
Cited alongside, same era.
“A Review of Tactile Information: Perception and Action Through Touch”
Qiang Li, Oliver Kroemer, Zhe Su, Filipe Veiga, Mohsen Kaboli and Helge Ritter · 2020
Later among the works it cites.
“Learning Hierarchical Control for Robust In-Hand Manipulation”
Tingguang Li, Krishnan Srinivasan, Max-Hu Meng, Wenzhen Yuan and Jeannette Bohg · 2020
Later among the works it cites.
“Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks”
Filipe Veiga, Riad Akrour and Jan Peters · 2020
Later among the works it cites.
“Deep dynamics models for learning dexterous manipulation”
A Nagabandi, K Konolige and S Levine · 2020
Later among the works it cites.
“Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs”
Fan Shi, Timon Homberger, Joonho Lee, Takahiro Miki, Moju Zhao, Farbod Farshidian, Kei Okada, Masayuki Inaba and Marco Hutter · 2021
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“Geometric In-Hand Regrasp Planning: Alternating Optimization of Finger Gaits and In-Grasp Manipulation”
Balakumar Sundaralingam and Tucker Hermans · 2018
Cited alongside, same era.
“Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations”
Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, Giulia Vezzani, John Schulman, Emanuel Todorov and Sergey Levine · 2018
Cited alongside, same era.
“Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost”
Henry Zhu, Abhishek Gupta, Aravind Rajeswaran, Sergey Levine and Vikash Kumar · 2019
Cited alongside, same era.
“Learning dexterous in-hand manipulation”
OpenAI: Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Józefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, Jonas Schneider, Szymon Sidor, Josh Tobin, Peter Welinder, Lilian Weng and Wojciech Zaremba · 2020
Cited alongside, same era.
Andrew. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D’Eramo, Aaron. Dollar and Jan Peters · 2021
Closest in time.
“State-Only Imitation Learning for Dexterous Manipulation”
Ilija Radosavovic, Xiaolong Wang, Lerrel Pinto and Jitendra Malik · 2021
Closest in time.
“Using Tactile Sensing to Improve the Sample Efficiency and Performance of Deep Deterministic Policy Gradients for Simulated In-Hand Manipulation Tasks”
Andrew Melnik, Luca Lach, Matthias Plappert, Timo Korthals, Robert Haschke and Helge Ritter · 2021
Closest in time.
“A Simple Method for Complex In-hand Manipulation”
Tao Chen, Jie Xu and Pulkit Agrawal · 2021
Closest in time.