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We introduce RotateIt, a system that enables fingertip-based object rotation along multiple axes by leveraging multimodal sensory inputs.
Solving rubik’s cube with a robot hand
OpenAI, I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, J. Schneider, N. Tezak, J. Tworek, P. Welinder, L. Weng, Q. Yuan, W. Zaremba, and L. Zhang · 1910
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Factors influencing the force control during precision grip
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Implementing a force strategy for object re-orientation
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Dextrous manipulation by rolling and finger gaiting
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In-hand dexterous manipulation of piecewise-smooth 3-d objects
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Dexterous manipulation planning using probabilistic roadmaps in continuous grasp subspaces
J.-P. Saut, A. Sahbani, S. El-Khoury, and V. Perdereau · 2007
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Coding and use of tactile signals from the fingertips in object manipulation tasks
R. S. Johansson and J. R. Flanagan · 2009
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Contact-invariant optimization for hand manipulation
I. Mordatch, Z. Popović, and E. Todorov · 2012
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Allegrohand
WonikRobotics · 2013
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Dexterous manipulation using both palm and fingers
Y. Bai and C. K. Liu · 2014
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Learning object-level impedance control for robust grasping and dexterous manipulation
M. Li, H. Yin, K. Tahara, and A. Billard · 2014
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Learning robot in-hand manipulation with tactile features
H. Van Hoof, T. Hermans, G. Neumann, and J. Peters · 2015
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The ycb object and model set: Towards common benchmarks for manipulation research
B. Calli, A. Singh, A. Walsman, S. Srinivasa, P. Abbeel, and A. M. Dollar · 2015
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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Robust reconstruction of indoor scenes
S. Choi, Q.-Y. Zhou, and V. Koltun · 2015
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Fast and accurate deep network learning by exponential linear units (elus)
D.-A. Clevert, T. Unterthiner, and S. Hochreiter · 2015
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Learning dexterous manipulation for a soft robotic hand from human demonstrations
A. Gupta, C. Eppner, S. Levine, and P. Abbeel · 2016
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Gelsight: High-resolution robot tactile sensors for estimating geometry and force
W. Yuan, S. Dong, and E. H. Adelson · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2017
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Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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The tactip family: Soft optical tactile sensors with 3d-printed biomimetic morphologies
B. Ward-Cherrier, N. Pestell, L. Cramphorn, B. Winstone, M. E. Giannaccini, J. Rossiter, and N. F. Lepora · 2018
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More than a feeling: Learning to grasp and regrasp using vision and touch
R. Calandra, A. Owens, D. Jayaraman, W. Yuan, J. Lin, J. Malik, E. H. Adelson, and S. Levine · 2018
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Speeded up detection of squared fiducial markers
F. J. Romero-Ramirez, R. Muñoz-Salinas, and R. Medina-Carnicer · 2018
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Deep dynamics models for learning dexterous manipulation
A. Nagabandi, K. Konolige, S. Levine, and V. Kumar · 2019
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Contactdb: Analyzing and predicting grasp contact via thermal imaging
S. Brahmbhatt, C. Ham, C. C. Kemp, and J. Hays · 2019
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Learning quadrupedal locomotion over challenging terrain
J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter · 2020
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Se(3)-tracknet: Data-driven 6d pose tracking by calibrating image residuals in synthetic domains
B. Wen, C. Mitash, B. Ren, and K. E. Bekris · 2020
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Egad! an evolved grasping analysis dataset for diversity and reproducibility in robotic manipulation
D. Morrison, P. Corke, and J. Leitner · 2020
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Learning by cheating
D. Chen, B. Zhou, V. Koltun, and P. Krähenbühl · 2020
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Digit: A novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation
M. Lambeta, P.-W. Chou, S. Tian, B. Yang, B. Maloon, V. R. Most, D. Stroud, R. Santos, A. Byagowi, G. Kammerer, et al · 2020
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Geltip: A finger-shaped optical tactile sensor for robotic manipulation
D. F. Gomes, Z. Lin, and S. Luo · 2020
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3d shape reconstruction from vision and touch
Masked visual pre-training for motor control
T. Xiao, I. Radosavovic, T. Darrell, and J. Malik · 2022
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Rt-1: Robotics transformer for real-world control at scale
A. Brohan, N. Brown, J. Carbajal, Y. Chebotar, J. Dabis, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, J. Hsu, et al · 2022
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Viola: Imitation learning for vision-based manipulation with object proposal priors
Y. Zhu, A. Joshi, P. Stone, and Y. Zhu · 2022
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Learning vision-guided quadrupedal locomotion end-to-end with cross-modal transformers
R. Yang, M. Zhang, N. Hansen, H. Xu, and X. Wang · 2022
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Vima: General robot manipulation with multimodal prompts
Y. Jiang, A. Gupta, Z. Zhang, G. Wang, Y. Dou, Y. Chen, L. Fei-Fei, A. Anandkumar, Y. Zhu, and L. Fan · 2022
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E. Smith, R. Calandra, A. Romero, G. Gkioxari, D. Meger, J. Malik, and M. Drozdzal · 2020
Cited alongside, same era.
Rma: Rapid motor adaptation for legged robots
A. Kumar, Z. Fu, D. Pathak, and J. Malik · 2021
Cited alongside, same era.
A system for general in-hand object re-orientation
T. Chen, J. Xu, and P. Agrawal · 2021
Cited alongside, same era.
Generalization in dexterous manipulation via geometry-aware multi-task learning
W. Huang, I. Mordatch, P. Abbeel, and D. Pathak · 2021
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Learning high-speed flight in the wild
A. Loquercio, E. Kaufmann, R. Ranftl, M. Müller, V. Koltun, and D. Scaramuzza · 2021
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Active 3d shape reconstruction from vision and touch
E. Smith, D. Meger, L. Pineda, R. Calandra, J. Malik, A. Romero Soriano, and M. Drozdzal · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, et al · 2021
Cited alongside, same era.
Visuo-tactile transformers for manipulation
Y. Chen, A. Sipos, M. Van der Merwe, and N. Fazeli · 2022
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Unpacking reward shaping: Understanding the benefits of reward engineering on sample complexity
A. Gupta, A. Pacchiano, Y. Zhai, S. Kakade, and S. Levine · 2022
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Computational benefits of intermediate rewards for goal-reaching policy learning
Y. Zhai, C. Baek, Z. Zhou, J. Jiao, and Y. Ma · 2022
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Legged locomotion in challenging terrains using egocentric vision
A. Agarwal, A. Kumar, J. Malik, and D. Pathak · 2022
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Dexpoint: Generalizable point cloud reinforcement learning for sim-to-real dexterous manipulation
Y. Qin, B. Huang, Z.-H. Yin, H. Su, and X. Wang · 2022
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Dextreme: Transfer of agile in-hand manipulation from simulation to reality
A. Handa, A. Allshire, V. Makoviychuk, A. Petrenko, R. Singh, J. Liu, D. Makoviichuk, K. Van Wyk, A. Zhurkevich, B. Sundaralingam, Y. Narang, J.-F. Lafleche, D. Fox, and G. State · 2023
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Dextrous tactile in-hand manipulation using a modular reinforcement learning architecture
J. Pitz, L. Röstel, L. Sievers, and B. Bäuml · 2023
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Segment anything
A. Kirillov, E. Mintun, N. Ravi, H. Mao, C. Rolland, L. Gustafson, T. Xiao, S. Whitehead, A. C. Berg, W.-Y. Lo, et al · 2023
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Faster segment anything: Towards lightweight sam for mobile applications
C. Zhang, D. Han, Y. Qiao, J. U. Kim, S.-H. Bae, S. Lee, and C. S. Hong · 2023
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Dexterous imitation made easy: A learning-based framework for efficient dexterous manipulation
S. P. Arunachalam, S. Silwal, B. Evans, and L. Pinto · 2023
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Rotating without seeing: Towards in-hand dexterity through touch
Z.-H. Yin, B. Huang, Y. Qin, Q. Chen, and X. Wang · 2023
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Sampling-based exploration for reinforcement learning of dexterous manipulation
G. Khandate, S. Shang, E. T. Chang, T. L. Saidi, J. Adams, and M. Ciocarlie · 2023
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Dtact: A vision-based tactile sensor that measures high-resolution 3d geometry directly from darkness
C. Lin, Z. Lin, S. Wang, and H. Xu · 2023
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Arraybot: Reinforcement learning for generalizable distributed manipulation through touch
Z. Xue, H. Zhang, J. Cheng, Z. He, Y. Ju, C. Lin, G. Zhang, and H. Xu · 2023
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Allsight: A low-cost and high-resolution round tactile sensor with zero-shot learning capability
O. Azulay, N. Curtis, R. Sokolovsky, G. Levitski, D. Slomovik, G. Lilling, and A. Sintov · 2023
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Robopianist: A benchmark for high-dimensional robot control
K. Zakka, L. Smith, N. Gileadi, T. Howell, X. B. Peng, S. Singh, Y. Tassa, P. Florence, A. Zeng, and P. Abbeel · 2023
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Dexterity from touch: Self-supervised pre-training of tactile representations with robotic play
I. Guzey, B. Evans, S. Chintala, and L. Pinto · 2023
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See to touch: Learning tactile dexterity through visual incentives
I. Guzey, Y. Dai, B. Evans, S. Chintala, and L. Pinto · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
T. Z. Zhao, V. Kumar, S. Levine, and C. Finn · 2023
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Learning humanoid locomotion with transformers
I. Radosavovic, T. Xiao, B. Zhang, T. Darrell, J. Malik, and K. Sreenath · 2023
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Dexart: Benchmarking generalizable dexterous manipulation with articulated objects
C. Bao, H. Xu, Y. Qin, and X. Wang · 2023
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Understanding the complexity gains of single-task rl with a curriculum
Q. Li, Y. Zhai, Y. Ma, and S. Levine · 2023
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