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Robot-assisted dressing could benefit the lives of many people such as older adults and individuals with disabilities.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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User modelling for personalised dressing assistance by humanoid robots
Yixing Gao, Hyung Jin Chang, and Yiannis Demiris · 2015
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Actor-mimic: Deep multitask and transfer reinforcement learning
Emilio Parisotto, Jimmy Lei Ba, and Ruslan Salakhutdinov · 2015
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Andrei A Rusu, Sergio Gomez Colmenarejo, Caglar Gulcehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, and Raia Hadsell · 2015
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Iterative path optimisation for personalised dressing assistance using vision and force information
Yixing Gao, Hyung Jin Chang, and Yiannis Demiris · 2016
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Data-driven haptic perception for robot-assisted dressing
Ariel Kapusta, Wenhao Yu, Tapomayukh Bhattacharjee, C Karen Liu, Greg Turk, and Charles C Kemp · 2016
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What does the person feel? learning to infer applied forces during robot-assisted dressing
Zackory Erickson, Alexander Clegg, Wenhao Yu, Greg Turk, C Karen Liu, and Charles C Kemp · 2017
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Haptic simulation for robot-assisted dressing
Wenhao Yu, Ariel Kapusta, Jie Tan, Charles C Kemp, Greg Turk, and C Karen Liu · 2017
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Personalized robot-assisted dressing using user modeling in latent spaces
Fan Zhang, Antoine Cully, and Yiannis Demiris · 2017
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Deep haptic model predictive control for robot-assisted dressing
Zackory Erickson, Henry M Clever, Greg Turk, C Karen Liu, and Charles C Kemp · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Personalized robot assistant for support in dressing
Aleksandar Jevtić, Andrés Flores Valle, Guillem Alenyà, Greg Chance, Praminda Caleb-Solly, Sanja Dogramadzi, and Carme Torras · 2018
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Kickstarting deep reinforcement learning
Simon Schmitt, Jonathan J Hudson, Augustin Zidek, Simon Osindero, Carl Doersch, Wojciech M Czarnecki, Joel Z Leibo, Heinrich Kuttler, Andrew Zisserman, Karen Simonyan, et al · 2018
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Learning synergies between pushing and grasping with self-supervised deep reinforcement learning
Andy Zeng, Shuran Song, Stefan Welker, Johnny Lee, Alberto Rodriguez, and Thomas Funkhouser · 2018
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Adapting robot task planning to user preferences: an assistive shoe dressing example
Gerard Canal, Guillem Alenyà, and Carme Torras · 2019
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Multidimensional capacitive sensing for robot-assisted dressing and bathing
Zackory Erickson, Henry M Clever, Vamsee Gangaram, Greg Turk, C Karen Liu, and Charles C Kemp · 2019
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Fast graph representation learning with PyTorch Geometric
Matthias Fey and Jan E. Lenssen · 2019
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Long-term care providers and services users in the united states, 2015-2016
Lauren D Harris-Kojetin, Manisha Sengupta, Jessica Penn Lendon, Vincent Rome, Roberto Valverde, and Christine Caffrey · 2019
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Personalized collaborative plans for robot-assisted dressing via optimization and simulation
Ariel Kapusta, Zackory Erickson, Henry M Clever, Wenhao Yu, C Karen Liu, Greg Turk, and Charles C Kemp · 2019
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Expressive body capture: 3D hands, face, and body from a single image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas, and Michael J. Black · 2019
Cited alongside, same era.
Deep transfer learning of pick points on fabric for robot bed-making
Daniel Seita, Nawid Jamali, Michael Laskey, Ajay Kumar Tanwani, Ron Berenstein, Prakash Baskaran, Soshi Iba, John Canny, and Ken Goldberg · 2019
Cited alongside, same era.
Learning to manipulate deformable objects without demonstrations
Yilin Wu, Wilson Yan, Thanard Kurutach, Lerrel Pinto, and Pieter Abbeel · 2019
Cited alongside, same era.
Probabilistic real-time user posture tracking for personalized robot-assisted dressing
Fan Zhang, Antoine Cully, and Yiannis Demiris · 2019
Cited alongside, same era.
Cloth3d: clothed 3d humans
Hugo Bertiche, Meysam Madadi, and Sergio Escalera · 2020
Cited alongside, same era.
Cloth funnels: Canonicalized-alignment for multi-purpose garment manipulation
Alper Canberk, Cheng Chi, Huy Ha, Benjamin Burchfiel, Eric Cousineau, Siyuan Feng, and Shuran Song · 2022
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Autobag: Learning to open plastic bags and insert objects
Lawrence Yunliang Chen, Baiyu Shi, Daniel Seita, Richard Cheng, Thomas Kollar, David Held, and Ken Goldberg · 2022
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Flowbot3d: Learning 3d articulation flow to manipulate articulated objects
Ben Eisner, Harry Zhang, and David Held · 2022
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Flingbot: The unreasonable effectiveness of dynamic manipulation for cloth unfolding
Huy Ha and Shuran Song · 2022
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Learning to collaborate from simulation for robot-assisted dressing
Alexander Clegg, Zackory Erickson, Patrick Grady, Greg Turk, Charles C Kemp, and C Karen Liu · 2020
Cited alongside, same era.
Spatial action maps for mobile manipulation
Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Johnny Lee, Szymon Rusinkiewicz, and Thomas Funkhouser · 2020
Cited alongside, same era.
Gradient surgery for multi-task learning
Tianhe Yu, Saurabh Kumar, Abhishek Gupta, Sergey Levine, Karol Hausman, and Chelsea Finn · 2020
Cited alongside, same era.
Learning grasping points for garment manipulation in robot-assisted dressing
Fan Zhang and Yiannis Demiris · 2020
Cited alongside, same era.
Generalization in dexterous manipulation via geometry-aware multi-task learning
Wenlong Huang, Igor Mordatch, Pieter Abbeel, and Deepak Pathak · 2021
Cited alongside, same era.
Exploiting symmetry in human robot-assisted dressing using reinforcement learning
Pedro Ildefonso, Pedro Remédios, Rui Silva, Miguel Vasco, Francisco S Melo, Ana Paiva, and Manuela Veloso · 2021
Cited alongside, same era.
Learning arbitrary-goal fabric folding with one hour of real robot experience
Robert Lee, Daniel Ward, Vibhavari Dasagi, Akansel Cosgun, Juxi Leitner, and Peter Corke · 2021
Cited alongside, same era.
Nicklas Hansen, Xiaolong Wang, and Hao Su · 2022
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Visuospatial foresight for physical sequential fabric manipulation
Ryan Hoque, Daniel Seita, Ashwin Balakrishna, Aditya Ganapathi, Ajay Kumar Tanwani, Nawid Jamali, Katsu Yamane, Soshi Iba, and Ken Goldberg · 2022
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Frame mining: a free lunch for learning robotic manipulation from 3d point clouds
Minghua Liu, Xuanlin Li, Zhan Ling, Yangyan Li, and Hao Su · 2022
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Tax-pose: Task-specific cross-pose estimation for robot manipulation
Chuer Pan, Brian Okorn, Harry Zhang, Ben Eisner, and David Held · 2022
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Bodies uncovered: Learning to manipulate real blankets around people via physics simulations
Kavya Puthuveetil, Charles C Kemp, and Zackory Erickson · 2022
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Cross-domain representation learning for clothes unfolding in robot-assisted dressing
Jinge Qie, Yixing Gao, Runyang Feng, Xin Wang, Jielong Yang, Esha Dasgupta, Hyung Jin Chang, and Yi Chang · 2022
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Dexpoint: Generalizable point cloud reinforcement learning for sim-to-real dexterous manipulation
Yuzhe Qin, Binghao Huang, Zhao-Heng Yin, Hao Su, and Xiaolong Wang · 2022
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Toolflownet: Robotic manipulation with tools via predicting tool flow from point clouds
Daniel Seita, Yufei Wang, Sarthak J Shetty, Edward Yao Li, Zackory Erickson, and David Held · 2022
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Fabricflownet: Bimanual cloth manipulation with a flow-based policy
Thomas Weng, Sujay Man Bajracharya, Yufei Wang, Khush Agrawal, and David Held · 2022
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Learning generalizable dexterous manipulation from human grasp affordance
Yueh-Hua Wu, Jiashun Wang, and Xiaolong Wang · 2022
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Dextairity: Deformable manipulation can be a breeze
Zhenjia Xu, Cheng Chi, Benjamin Burchfiel, Eric Cousineau, Siyuan Feng, and Shuran Song · 2022
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Learning garment manipulation policies toward robot-assisted dressing
Fan Zhang and Yiannis Demiris · 2022
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Challenges and outlook in robotic manipulation of deformable objects
Jihong Zhu, Andrea Cherubini, Claire Dune, David Navarro-Alarcon, Farshid Alambeigi, Dmitry Berenson, Fanny Ficuciello, Kensuke Harada, Jens Kober, Xiang Li, et al · 2022
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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