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Teaching dexterity to multi-fingered robots has been a longstanding challenge in robotics.
Making sense of vision and touch: Learning multimodal representations for contact-rich tasks, 2019
Michelle A. Lee, Yuke Zhu, Peter Zachares, Matthew Tan, Krishnan Srinivasan, Silvio Savarese, Li Fei-Fei, Animesh Garg, and Jeannette Bohg · 1907
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Cable manipulation with a tactile-reactive gripper, 2019
Yu She, Shaoxiong Wang, Siyuan Dong, Neha Sunil, Alberto Rodriguez, and Edward Adelson · 1910
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Object manipulation and exploration in 2-to 5-month-old infants
Philippe Rochat · 1989
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Somatosensory control of precision grip during unpredictable pulling loads: Iii. impairments during digital anesthesia
Roland S Johansson, Charlotte Häger, and Lars Bäckström · 1992
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An overview of dexterous manipulation
Allison M Okamura, Niels Smaby, and Mark R Cutkosky · 2000
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2002
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The grasp and other primitive reflexes
J M Schott · 2003
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Dynamic pen spinning using a high-speed multifingered hand with high-speed tactile sensor
Tatsuya Ishihara, Akio Namiki, Masatoshi Ishikawa, and Makoto Shimojo · 2006
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Dexterous grasping via eigengrasps : A low-dimensional approach to a high-complexity problem
Matei T. Ciocarlie, Corey Goldfeder, and Peter K. Allen · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Bryan Chen, Alexander Sax, Gene Lewis, Iro Armeni, Silvio Savarese, Amir Zamir, Jitendra Malik, and Lerrel Pinto · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Contact-invariant optimization for hand manipulation
Igor Mordatch, Zoran Popović, and Emanuel Todorov · 2012
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Real-time behaviour synthesis for dynamic hand-manipulation
Vikash Kumar, Yuval Tassa, Tom Erez, and Emanuel Todorov · 2014
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A compliant, underactuated hand for robust manipulation
Lael U Odhner, Leif P Jentoft, Mark R Claffee, Nicholas Corson, Yaroslav Tenzer, Raymond R Ma, Martin Buehler, Robert Kohout, Robert D Howe, and Aaron M Dollar · 2014
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Deep spatial autoencoders for visuomotor learning
Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, and Pieter Abbeel · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Optimal control with learned local models: Application to dexterous manipulation
Vikash Kumar, Emanuel Todorov, and Sergey Levine · 2016
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The curious robot: Learning visual representations via physical interactions
Lerrel Pinto, Dhiraj Gandhi, Yuanfeng Han, Yong-Lae Park, and Abhinav Gupta · 2016
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Improved gelsight tactile sensor for measuring geometry and slip
Siyuan Dong, Wenzhen Yuan, and Edward H Adelson · 2017
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More than a feeling: Learning to grasp and regrasp using vision and touch
Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H Adelson, and Sergey Levine · 2018
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Fetal origin of sensorimotor behavior
Jaqueline Fagard, Rana Esseily, Lisa Jacquey, Kevin O’Regan, and Eszter Somogyi · 2018
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Dense object nets: Learning dense visual object descriptors by and for robotic manipulation
Peter R Florence, Lucas Manuelli, and Russ Tedrake · 2018
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David Ha and Jürgen Schmidhuber · 2018
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It's the journey, not the destination: Locomotor exploration in infants
Justine E. Hoch, Sinclaire M. O'Grady, and Karen E. Adolph · 2018
Cited alongside, same era.
Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system
Kendall Lowrey, Svetoslav Kolev, Jeremy Dao, Aravind Rajeswaran, and Emanuel Todorov · 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.
Time-contrastive networks: Self-supervised learning from video
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine, and Google Brain · 2018
Cited alongside, same era.
ASIMO and Humanoid Robot Research at Honda , pages 1–36
Satoshi Shigemi · 2018
Cited alongside, same era.
Generalization in dexterous manipulation via geometry-aware multi-task learning
Wenlong Huang, Igor Mordatch, Pieter Abbeel, and Deepak Pathak · 2021
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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The surprising effectiveness of representation learning for visual imitation, 2021
Jyothish Pari, Nur Muhammad Shafiullah, Sridhar Pandian Arunachalam, and Lerrel Pinto · 2021
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Digger finger: Gelsight tactile sensor for object identification inside granular media
Radhen Patel, Rui Ouyang, Branden Romero, and Edward Adelson · 2021
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Reinforcement learning with prototypical representations
Denis Yarats, Rob Fergus, Alessandro Lazaric, and Lerrel Pinto · 2021
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A new silicone structure for uskin—a soft, distributed, digital 3-axis skin sensor and its integration on the humanoid robot icub
Tito Pradhono Tomo, Massimo Regoli, Alexander Schmitz, Lorenzo Natale, Harris Kristanto, Sophon Somlor, Lorenzo Jamone, Giorgio Metta, and Shigeki Sugano · 2018
Cited alongside, same era.
3d shape perception from monocular vision, touch, and shape priors
Shaoxiong Wang, Jiajun Wu, Xingyuan Sun, Wenzhen Yuan, William T Freeman, Joshua B Tenenbaum, and Edward H Adelson · 2018
Cited alongside, same era.
Soft-bubble: A highly compliant dense geometry tactile sensor for robot manipulation
Alex Alspach, Kunimatsu Hashimoto, Naveen Kuppuswamy, and Russ Tedrake · 2019
Cited alongside, same era.
Large-area soft e-skin: The challenges beyond sensor designs
Ravinder Dahiya, Nivasan Yogeswaran, Fengyuan Liu, Libu Manjakkal, Etienne Burdet, Vincent Hayward, and Henrik Jörntell · 2019
Cited alongside, same era.
Learning latent plans from play, 2019
Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, and Pierre Sermanet · 2019
Cited alongside, same era.
Deep dynamics models for learning dexterous manipulation
Anusha Nagabandi, Kurt Konoglie, Sergey Levine, and Vikash Kumar · 2019
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.
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Playful interactions for representation learning
Sarah Young, Jyothish Pari, Pieter Abbeel, and Lerrel Pinto · 2021
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Learning rich touch representations through cross-modal self-supervision
Martina Zambelli, Yusuf Aytar, Francesco Visin, Yuxiang Zhou, and Raia Hadsell · 2021
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Crosspoint: Self-supervised cross-modal contrastive learning for 3d point cloud understanding
Mohamed Afham, Isuru Dissanayake, Dinithi Dissanayake, Amaya Dharmasiri, Kanchana Thilakarathna, and Ranga Rodrigo · 2022
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David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, and Jake Varley · 2022
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From play to policy: Conditional behavior generation from uncurated robot data
Zichen Jeff Cui, Yibin Wang, Nur Muhammad, Lerrel Pinto, et al · 2022
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Self-supervised representation learning: Introduction, advances, and challenges
Linus Ericsson, Henry Gouk, Chen Change Loy, and Timothy M Hospedales · 2022
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Implicit behavioral cloning
Pete Florence, Corey Lynch, Andy Zeng, Oscar A Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, and Jonathan Tompson · 2022
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Dextreme: Transfer of agile in-hand manipulation from simulation to reality
Ankur Handa, Arthur Allshire, Viktor Makoviychuk, Aleksei Petrenko, Ritvik Singh, Jingzhou Liu, Denys Makoviichuk, Karl Van Wyk, Alexander Zhurkevich, Balakumar Sundaralingam, Yashraj Narang, Jean-Francois Lafleche, Dieter Fox, and Gavriel State · 2022
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Tactile pose estimation and policy learning for unknown object manipulation
Tarik Kelestemur, Robert Platt, and Taskin Padir · 2022
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Justin Kerr, Huang Huang, Albert Wilcox, Ryan Hoque, Jeffrey Ichnowski, Roberto Calandra, and Ken Goldberg · 2022
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R3m: A universal visual representation for robot manipulation
Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, and Abhinav Gupta · 2022
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BYOL for Audio: Exploring pre-trained general-purpose audio representations
Daisuke Niizumi, Daiki Takeuchi, Yasunori Ohishi, Noboru Harada, and Kunio Kashino · 2022
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Real-world robot learning with masked visual pre-training, 2022
Ilija Radosavovic, Tete Xiao, Stephen James, Pieter Abbeel, Jitendra Malik, and Trevor Darrell · 2022
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Behavior transformers: Cloning $k$ modes with one stone
Nur Muhammad Mahi Shafiullah, Zichen Jeff Cui, Ariuntuya Altanzaya, and Lerrel Pinto · 2022
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Learning purely tactile in-hand manipulation with a torque-controlled hand
Leon Sievers, Johannes Pitz, and Berthold Bäuml · 2022
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Don’t change the algorithm, change the data: Exploratory data for offline reinforcement learning
Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, and Lerrel Pinto · 2022
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Train offline, test online: A real robot learning benchmark
Gaoyue Zhou, Victoria Dean, Mohan Kumar Srirama, Aravind Rajeswaran, Jyothish Pari, Kyle Beltran Hatch, Aryan Jain, Tianhe Yu, Pieter Abbeel, Lerrel Pinto, Chelsea Finn, and Abhinav Gupta · 2022
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Viola: Imitation learning for vision-based manipulation with object proposal priors
Yifeng Zhu, Abhishek Joshi, Peter Stone, and Yuke Zhu · 2022
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