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Several robot manipulation tasks are extremely sensitive to variations of the physical properties of the manipulated objects.
Y. Chebotar, K. Hausman, Z. Su, G. S. Sukhatme, and S. Schaal, “Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning,” in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2016, pp. 1960–1966
1966
Earlier work this paper cites.
S. J. Lederman and R. L. Klatzky, “Hand movements: A window into haptic object recognition,” Cognitive psychology , vol. 19, no. 3, pp. 342–368, 1987
1987
Earlier work this paper cites.
S. Wold, K. Esbensen, and P. Geladi, “Principal component analysis,” Chemometrics and intelligent laboratory systems , vol. 2, no. 1-3, pp. 37–52, 1987
1987
Earlier work this paper cites.
M. T. Mason and K. M. Lynch, “Dynamic manipulation,” in Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’93) , vol. 1. IEEE, 1993, pp. 152–159
1993
Earlier work this paper cites.
S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural computation , vol. 9, no. 8, pp. 1735–1780, 1997
1997
Earlier work this paper cites.
T. Albahkali, R. Mukherjee, and T. Das, “Swing-up control of the pendubot: an impulse–momentum approach,” IEEE Transactions on Robotics , vol. 25, no. 4, pp. 975–982, 2009
2009
Earlier work this paper cites.
H. Dang and P. K. Allen, “Grasp adjustment on novel objects using tactile experience from similar local geometry,” in 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2013, pp. 4007–4012
2013
Earlier work this paper cites.
N. C. Dafle, A. Rodriguez, R. Paolini, B. Tang, S. S. Srinivasa, M. Erdmann, M. T. Mason, I. Lundberg, H. Staab, and T. Fuhlbrigge, “Extrinsic dexterity: In-hand manipulation with external forces,” in 2014 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2014, pp. 1578–1585
2014
Earlier work this paper cites.
J. Wu, I. Yildirim, J. J. Lim, B. Freeman, and J. Tenenbaum, “Galileo: Perceiving physical object properties by integrating a physics engine with deep learning,” in Advances in neural information processing systems , 2015, pp. 127–135
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
A. Sintov, O. Tslil, and A. Shapiro, “Robotic swing-up regrasping manipulation based on the impulse–momentum approach and clqr control,” IEEE Transactions on Robotics , vol. 32, no. 5, pp. 1079–1090, 2016
2016
Cited alongside, same era.
P. Agrawal, A. V. Nair, P. Abbeel, J. Malik, and S. Levine, “Learning to poke by poking: Experiential learning of intuitive physics,” in Advances in neural information processing systems , 2016, pp. 5074–5082
2016
Cited alongside, same era.
2016
Cited alongside, same era.
W. Yuan, S. Dong, and E. H. Adelson, “Gelsight: High-resolution robot tactile sensors for estimating geometry and force,” Sensors , vol. 17, no. 12, p. 2762, 2017
2017
Cited alongside, same era.
F. R. Hogan, M. Bauza, O. Canal, E. Donlon, and A. Rodriguez, “Tactile regrasp: Grasp adjustments via simulated tactile transformations,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 2963–2970
2018
Later among the works it cites.
M. Bauza, F. Alet, Y. Lin, T. Lozano-Perez, L. Kaelbling, P. Isola, and A. Rodriguez, “Omnipush: accurate, diverse, real-world dataset of pushing dynamics with rgbd images,” in NeurIPS Physics Workshop , 2018
2018
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
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J. Shi, J. Z. Woodruff, P. B. Umbanhowar, and K. M. Lynch, “Dynamic in-hand sliding manipulation,” IEEE Transactions on Robotics , vol. 33, no. 4, pp. 778–795, 2017
2017
Cited alongside, same era.
C. Finn and S. Levine, “Deep visual foresight for planning robot motion,” in 2017 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2017, pp. 2786–2793
2017
Cited alongside, same era.
R. B. Hellman, C. Tekin, M. van der Schaar, and V. J. Santos, “Functional contour-following via haptic perception and reinforcement learning,” IEEE transactions on haptics , vol. 11, no. 1, pp. 61–72, 2017
2017
Cited alongside, same era.
R. Calandra, A. Owens, D. Jayaraman, J. Lin, W. Yuan, J. Malik, E. H. Adelson, and S. Levine, “More than a feeling: Learning to grasp and regrasp using vision and touch,” IEEE Robotics and Automation Letters , vol. 3, no. 4, pp. 3300–3307, 2018
2018
Cited alongside, same era.
F. Veiga, J. Peters, and T. Hermans, “Grip stabilization of novel objects using slip prediction,” IEEE transactions on haptics , vol. 11, no. 4, pp. 531–542, 2018
2018
Cited alongside, same era.
S. Stepputtis, Y. Yang, and H. B. Amor, “Extrinsic dexterity through active slip control using deep predictive models,” in 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2018, pp. 3180–3185
2018
Cited alongside, same era.
2019
Later among the works it cites.
S. Dong, D. Ma, E. Donlon, and A. Rodriguez, “Maintaining grasps within slipping bounds by monitoring incipient slip,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 3818–3824
2019
Later among the works it cites.
N. F. Lepora, A. Church, C. De Kerckhove, R. Hadsell, and J. Lloyd, “From pixels to percepts: Highly robust edge perception and contour following using deep learning and an optical biomimetic tactile sensor,” IEEE Robotics and Automation Letters , vol. 4, no. 2, pp. 2101–2107, 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
S. Tian, F. Ebert, D. Jayaraman, M. Mudigonda, C. Finn, R. Calandra, and S. Levine, “Manipulation by feel: Touch-based control with deep predictive models,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 818–824
2019
Later among the works it cites.