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We introduce Midas, a robotics simulation framework based on the Incremental Potential Contact (IPC) model.
H. M. Lankarani and P. E. Nikravesh, “A contact force model with hysteresis damping for impact analysis of multibody systems,” in International Design Engineering Technical Conferences and Computers and Information in Engineering Conference , vol. 3691. American Society of Mechanical Engineers, 1989, pp. 45–51
1989
Earlier work this paper cites.
L. B. Rosenberg, “Perceptual design of a virtual rigid surface contact.” Stanford University Center for Design Research, Tech. Rep., 1993
1993
Earlier work this paper cites.
D. Baraff, “Fast contact force computation for nonpenetrating rigid bodies,” in Proceedings of the 21st annual conference on Computer graphics and interactive techniques , 1994, pp. 23–34
1994
Earlier work this paper cites.
D. E. Stewart and J. C. Trinkle, “An implicit time-stepping scheme for rigid body dynamics with inelastic collisions and coulomb friction,” International Journal for Numerical Methods in Engineering , vol. 39, no. 15, pp. 2673–2691, 1996
1996
Earlier work this paper cites.
E. Todorov, “Implicit nonlinear complementarity: A new approach to contact dynamics,” in 2010 IEEE international conference on robotics and automation . IEEE, 2010, pp. 2322–2329
2010
Earlier work this paper cites.
E. Todorov, T. Erez, and Y. Tassa, “Mujoco: A physics engine for model-based control,” pp. 5026–5033, 2012
2012
Earlier work this paper cites.
E. Coumans, “Bullet physics simulation,” in ACM SIGGRAPH 2015 Courses , 2015, p. 1
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
J. Schulman, S. Levine, P. Abbeel, M. Jordan, and P. Moritz, “Trust region policy optimization,” in International conference on machine learning . PMLR, 2015, pp. 1889–1897
2015
Cited alongside, same era.
2016
Cited alongside, same era.
M. Li, Z. Ferguson, T. Schneider, T. R. Langlois, D. Zorin, D. Panozzo, C. Jiang, and D. M. Kaufman, “Incremental potential contact: intersection-and inversion-free, large-deformation dynamics.” ACM Trans. Graph. , vol. 39, no. 4, p. 49, 2020
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Y. Shi, Z. Chen, H. Liu, S. Riedel, C. Gao, Q. Feng, J. Deng, and J. Zhang, “Proactive action visual residual reinforcement learning for contact-rich tasks using a torque-controlled robot,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. 765–771
2021
Later among the works it cites.
J. Luo and H. Li, “A learning approach to robot-agnostic force-guided high precision assembly,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2021, pp. 2151–2157
2021
Later among the works it cites.
E. Coumans and Y. Bai, “Pybullet, a python module for physics simulation for games, robotics and machine learning,” http://pybullet.org, 2016–2021
2021
Later among the works it cites.
2022
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C. C. Beltran-Hernandez, D. Petit, I. G. Ramirez-Alpizar, and K. Harada, “Variable compliance control for robotic peg-in-hole assembly: A deep-reinforcement-learning approach,” Applied Sciences , vol. 10, no. 19, p. 6923, 2020
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Z. Ferguson, M. Li, T. Schneider, F. G. Ureta, T. R. Langlois, C. Jiang, D. Zorin, D. M. Kaufman, and D. Panozzo, “Intersection-free rigid body dynamics.” ACM Trans. Graph. , vol. 40, no. 4, pp. 183–1, 2021
2021
Cited alongside, same era.
Z. Xu, W. Yu, A. Herzog, W. Lu, C. Fu, M. Tomizuka, Y. Bai, C. K. Liu, and D. Ho, “Cocoi: Contact-aware online context inference for generalizable non-planar pushing,” pp. 176–182, 2021
2021
Cited alongside, same era.
“Open dynamics engine.” [Online]. Available: https://www.ode.org/
Cited in the paper.
“Physx physics engine.” [Online]. Available: https://developer.nvidia. com/physx-sdk
Cited in the paper.
Y. Chen, M. Li, L. Lan, H. Su, Y. Yang, and C. Jiang, “A unified newton barrier method for multibody dynamics,” ACM Transactions on Graphics (TOG) , vol. 41, no. 4, pp. 1–14, 2022
2022
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C. M. Kim, M. Danielczuk, I. Huang, and K. Goldberg, “Ipc-graspsim: Reducing the sim2real gap for parallel-jaw grasping with the incremental potential contact model,” in 2022 International Conference on Robotics and Automation (ICRA) . IEEE, 2022, pp. 6180–6187
2022
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H. Ichiwara, H. Ito, K. Yamamoto, H. Mori, and T. Ogata, “Contact-rich manipulation of a flexible object based on deep predictive learning using vision and tactility,” in 2022 International Conference on Robotics and Automation (ICRA) . IEEE, 2022, pp. 5375–5381
2022
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