Learning to Solve a Rubik's Cube with a Dexterous Hand

M. Thistlethwaite, “Thistlethwaite’s 52-move algorithm,” 1981

1981

Earlier work this paper cites.

A. H. Frey and D. Singmaster, Handbook of cubik math . Enslow Publishers Hillside, NJ, 1982

1982

Earlier work this paper cites.

R. E. Korf, “Finding optimal solutions to rubik’s cube using pattern databases,” in AAAI/IAAI , 1997, pp. 700–705

1997

Earlier work this paper cites.

C. Zieliński, W. Szynkiewicz, T. Winiarski, M. Staniak, W. Czajewski, and T. Kornuta, “Rubik’s cube as a benchmark validating mrroc++ as an implementation tool for service robot control systems,” Industrial Robot: An International Journal , vol. 34, no. 5, pp. 368–375, 2007

2007

Earlier work this paper cites.

D. Kunkle and G. Cooperman, “Harnessing parallel disks to solve rubik’s cube,” Journal of Symbolic Computation , vol. 44, no. 7, pp. 872–890, 2009

2009

Earlier work this paper cites.

I. Mordatch, Z. Popović, and E. Todorov, “Contact-invariant optimization for hand manipulation,” in Proceedings of the ACM SIGGRAPH/Eurographics symposium on computer animation . Eurographics Association, 2012, pp. 137–144

2012

Earlier work this paper cites.

E. Todorov, T. Erez, and Y. Tassa, “Mujoco: A physics engine for model-based control,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems . IEEE, 2012, pp. 5026–5033

2012

Earlier work this paper cites.

Y. Bai and C. K. Liu, “Dexterous manipulation using both palm and fingers,” in 2014 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2014, pp. 1560–1565

2014

Earlier work this paper cites.

T. Rokicki, H. Kociemba, M. Davidson, and J. Dethridge, “The diameter of the rubik’s cube group is twenty,” SIAM Review , vol. 56, no. 4, pp. 645–670, 2014

2014

Cited alongside, same era.

T. Erez, Y. Tassa, and E. Todorov, “Simulation tools for model-based robotics: Comparison of bullet, havok, mujoco, ode and physx,” in 2015 IEEE international conference on robotics and automation (ICRA) . IEEE, 2015, pp. 4397–4404

2015

Cited alongside, same era.

T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, and D. Wierstra, “Continuous control with deep reinforcement learning,” arXiv preprint arXiv:1509.02971 , 2015

Original

2015

Cited alongside, same era.

V. Kumar, E. Todorov, and S. Levine, “Optimal control with learned local models: Application to dexterous manipulation,” in 2016 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2016, pp. 378–383

2016

Cited alongside, same era.

M. Andrychowicz, F. Wolski, A. Ray, J. Schneider, R. Fong, P. Welinder, B. McGrew, J. Tobin, O. P. Abbeel, and W. Zaremba, “Hindsight experience replay,” in Advances in Neural Information Processing Systems , 2017, pp. 5048–5058

2017

Later among the works it cites.

M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B. McGrew, J. Pachocki, A. Petron, M. Plappert, G. Powell, A. Ray, et al. , “Learning dexterous in-hand manipulation,” arXiv preprint arXiv:1808.00177 , 2018

Original

2018

Later among the works it cites.

N. Chavan-Dafle, R. Holladay, and A. Rodriguez, “In-hand manipulation via motion cones,” arXiv preprint arXiv:1810.00219 , 2018

Original

2018

Later among the works it cites.

G. Barth-Maron, M. W. Hoffman, D. Budden, W. Dabney, D. Horgan, A. Muldal, N. Heess, and T. Lillicrap, “Distributed distributional deterministic policy gradients,” arXiv preprint arXiv:1804.08617 , 2018

Original

2018

Later among the works it cites.