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We present a controller that allows an arm-like manipulator to navigate deformable cloth garments in simulation through the use of haptic information.
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2014
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K. Yamazaki, R. Oya, K. Nagahama, K. Okada, and M. Inaba, “Bottom dressing by a life-sized humanoid robot provided failure detection and recovery functions,” in System Integration (SII), 2014 IEEE/SICE International Symposium on . IEEE, 2014, pp. 564–570
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2015
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F. Sygulla, C. Schuetz, and D. Rixen, “Adaptive motion control in uncertain environments using tactile feedback,” in Advanced Intelligent Mechatronics (AIM), 2016 IEEE International Conference on . IEEE, 2016, pp. 1277–1284
2016
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M. D. Killpack, A. Kapusta, and C. C. Kemp, “Model predictive control for fast reaching in clutter,” Autonomous Robots , vol. 40, no. 3, pp. 537–560, 2016
2016
Later among the works it cites.
A. Kapusta, W. Yu, T. Bhattacharjee, C. K. Liu, G. Turk, and C. C. Kemp, “Data-driven haptic perception for robot-assisted dressing,” in IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 2016
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2014
Cited alongside, same era.
E. Miguel, A. Feng, Y. Xu, A. Shapiro, R. Tamstorf, D. Bradley, S. C. Schvartzman, B. Thomaszewsky, B. Bickel, W. Matusik, et al. , “Towards cloth-manipulating characters,” in Computer Animation and Social Agents , vol. 3, 2014
2014
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C. Phillips-Grafflin and D. Berenson, “A representation of deformable objects for motion planning with no physical simulation,” in Robotics and Automation (ICRA), 2014 IEEE International Conference on . IEEE, 2014, pp. 98–105
2014
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M. Macklin, M. Müller, N. Chentanez, and T.-Y. Kim, “Unified particle physics for real-time applications,” ACM Trans. Graph. , vol. 33, no. 4, pp. 153:1–153:12, July 2014. [Online]. Available: http://doi.acm.org/10.1145/2601097.2601152
2014
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A. Clegg, J. Tan, G. Turk, and C. K. Liu, “Animating human dressing,” ACM Trans. Graph. , vol. 34, no. 4, pp. 116:1–116:9, July 2015. [Online]. Available: http://doi.acm.org/10.1145/2766986
2015
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2015
Cited alongside, same era.
2015
Cited alongside, same era.
2015
Cited alongside, same era.
“DART: Dynamic Animation and Robotics Toolkit”.” [Online]. Available: http://dartsim.github.io/
Cited in the paper.
2016
Later among the works it cites.
Y. Gao, H. Chang, and Y. Demiris, “Iterative path optimisation for personalised dressing assistance using vision and force information.” IEEE, 2016. [Online]. Available: http://hdl.handle.net/10044/1/39009
2016
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2016
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V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu, “Asynchronous methods for deep reinforcement learning,” in International Conference on Machine Learning , 2016
2016
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D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis, “Mastering the game of go with deep neural networks and tree search,” Nature , vol. 529, no. 7587, pp. 484–489, 01 2016. [Online]. Available: http://dx.doi.org/10.1038/nature16961
2016
Later among the works it cites.
W. Yu, A. Kapusta, J. Tan, C. C. Kemp, G. Turk, and C. K. Liu, “Haptic data simulation for robot-assisted dressing,” in 2017 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2017
2017
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Z. Erickson, A. Clegg, W. Yu, C. K. Liu, G. Turk, and C. C. Kemp, “What does the person feel? learning to infer applied forces during robot-assisted dressing,” in 2017 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2017
2017
Closest in time.