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Manipulating deformable objects, such as fabric, is a long standing problem in robotics, with state estimation and control posing a significant challenge for traditional methods.
Robust estimation of a location parameter
P. J. Huber · 1964
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Clothes folding task by tool-using robot
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Bringing clothing into desired configurations with limited perception
M. Cusumano-Towner, A. Singh, S. Miller, J. F. O’Brien, and P. Abbeel · 2011
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Model for unfolding laundry using interactive perception
B. Willimon, S. Birchfield, and I. Walker · 2011
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A heuristic-based approach for flattening wrinkled clothes
L. Sun, G. Aragon-Camarasa, P. Cockshott, S. Rogers, and J. P. Siebert · 2013
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Segmentation performance in tracking deformable objects via wnns
M. Staffa, S. Rossi, M. Giordano, M. De Gregorio, and B. Siciliano · 2015
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Accurate garment surface analysis using an active stereo robot head with application to dual-arm flattening
L. Sun, G. Aragon-Camarasa, S. Rogers, and J. P. Siebert · 2015
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Human-level control through deep reinforcement learning
V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al · 2015
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A multimodal model of object deformation under robotic pushing
V. E. Arriola-Rios and J. L. Wyatt · 2017
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Learning robust bed making using deep imitation learning with dart
M. Laskey, C. Powers, R. Joshi, A. Poursohi, and K. Goldberg · 2017
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Combining self-supervised learning and imitation for vision-based rope manipulation
A. Nair, D. Chen, P. Agrawal, P. Isola, P. Abbeel, J. Malik, and S. Levine · 2017
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Hindsight experience replay
M. Andrychowicz, F. Wolski, A. Ray, J. Schneider, R. Fong, P. Welinder, B. McGrew, J. Tobin, O. P. Abbeel, and W. Zaremba · 2017
Cited alongside, same era.
Cartman: The low-cost cartesian manipulator that won the amazon robotics challenge
D. Morrison, A. W. Tow, M. Mctaggart, R. Smith, N. Kelly-Boxall, S. Wade-Mccue, J. Erskine, R. Grinover, A. Gurman, T. Hunn, et al · 2018
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Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey
J. Sanchez, J.-A. Corrales, B.-C. Bouzgarrou, and Y. Mezouar · 2018
Cited alongside, same era.
Sim-to-real reinforcement learning for deformable object manipulation
J. Matas, S. James, and A. J. Davison · 2018
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Learning synergies between pushing and grasping with self-supervised deep reinforcement learning
A. Zeng, S. Song, S. Welker, J. Lee, A. Rodriguez, and T. Funkhouser · 2018
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Off-policy deep reinforcement learning without exploration
S. Fujimoto, D. Meger, and D. Precup · 2019
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Scaling data-driven robotics with reward sketching and batch reinforcement learning
S. Cabi, S. Gómez Colmenarejo, A. Novikov, K. Konyushkova, S. Reed, R. Jeong, K. Zolna, Y. Aytar, D. Budden, M. Vecerik, et al · 2019
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Learning robust, real-time, reactive robotic grasping
D. Morrison, P. Corke, and J. Leitner · 2020
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Learning dexterous in-hand manipulation
O. M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, et al · 2020
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Model-free vision-based shaping of deformable plastic materials
A. Cherubini, V. Ortenzi, A. Cosgun, R. Lee, and P. Corke · 2020
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Learning deployable navigation policies at kilometer scale from a single traversal
J. Bruce, N. Sünderhauf, P. Mirowski, R. Hadsell, and M. Milford · 2018
Cited alongside, same era.
Tossingbot: Learning to throw arbitrary objects with residual physics
A. Zeng, S. Song, J. Lee, A. Rodriguez, and T. Funkhouser · 2019
Cited alongside, same era.
Dynamic cloth manipulation with deep reinforcement learning
R. Jangir, G. Alenya, and C. Torras · 2019
Cited alongside, same era.
Learning to manipulate deformable objects without demonstrations
Y. Wu, W. Yan, T. Kurutach, L. Pinto, and P. Abbeel · 2019
Cited alongside, same era.
Deep imitation learning of sequential fabric smoothing policies
D. Seita, A. Ganapathi, R. Hoque, M. Hwang, E. Cen, A. K. Tanwani, A. Balakrishna, B. Thananjeyan, J. Ichnowski, N. Jamali, et al · 2019
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A. Ganapathi, P. Sundaresan, B. Thananjeyan, A. Balakrishna, D. Seita, J. Grannen, M. Hwang, R. Hoque, J. E. Gonzalez, N. Jamali, et al · 2020
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Visuospatial foresight for multi-step, multi-task fabric manipulation
R. Hoque, D. Seita, A. Balakrishna, A. Ganapathi, A. K. Tanwani, N. Jamali, K. Yamane, S. Iba, and K. Goldberg · 2020
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Learning predictive representations for deformable objects using contrastive estimation
W. Yan, A. Vangipuram, P. Abbeel, and L. Pinto · 2020
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Striving for simplicity in off-policy deep reinforcement learning, 2020
R. Agarwal, D. Schuurmans, and M. Norouzi · 2020
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Keep doing what worked: Behavioral modelling priors for offline reinforcement learning
N. Y. Siegel, J. T. Springenberg, F. Berkenkamp, A. Abdolmaleki, M. Neunert, T. Lampe, R. Hafner, and M. Riedmiller · 2020
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