BODex: Scalable and Efficient Robotic Dexterous Grasp Synthesis Using Bilevel Optimization

E. G. Gilbert, D. W. Johnson, and S. S. Keerthi, “A fast procedure for computing the distance between complex objects in three-dimensional space,” IEEE Journal on Robotics and Automation , vol. 4, no. 2, pp. 193–203, 1988

1988

Earlier work this paper cites.

C. Ferrari, J. F. Canny, et al. , “Planning optimal grasps.” in ICRA , vol. 3, no. 4, 1992, p. 6

1992

Earlier work this paper cites.

N. Xydas and I. Kao, “Modeling of contact mechanics and friction limit surfaces for soft fingers in robotics, with experimental results,” The International Journal of Robotics Research , vol. 18, no. 9, pp. 941–950, 1999

1999

Earlier work this paper cites.

A. T. Miller and P. K. Allen, “Graspit! a versatile simulator for robotic grasping,” IEEE Robotics & Automation Magazine , vol. 11, no. 4, pp. 110–122, 2004

2004

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.

D. P. Kingma, “Auto-encoding variational bayes,” arXiv preprint arXiv:1312.6114 , 2013

Original

2013

Earlier work this paper cites.

J. Schulman, Y. Duan, J. Ho, A. Lee, I. Awwal, H. Bradlow, J. Pan, S. Patil, K. Goldberg, and P. Abbeel, “Motion planning with sequential convex optimization and convex collision checking,” The International Journal of Robotics Research , vol. 33, no. 9, pp. 1251–1270, 2014

2014

Earlier work this paper cites.

D. Rezende and S. Mohamed, “Variational inference with normalizing flows,” in International conference on machine learning . PMLR, 2015, pp. 1530–1538

2015

Earlier work this paper cites.

B. Graham and L. Van der Maaten, “Submanifold sparse convolutional networks,” arXiv preprint arXiv:1706.01307 , 2017

Original

2017

Earlier work this paper cites.

H.-S. Fang, C. Wang, M. Gou, and C. Lu, “Graspnet-1billion: A large-scale benchmark for general object grasping,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2020, pp. 11 444–11 453

2020

Earlier work this paper cites.

B. Stellato, G. Banjac, P. Goulart, A. Bemporad, and S. Boyd, “Osqp: An operator splitting solver for quadratic programs,” Mathematical Programming Computation , vol. 12, no. 4, pp. 637–672, 2020

2020

Earlier work this paper cites.

M. Liu, Z. Pan, K. Xu, K. Ganguly, and D. Manocha, “Deep differentiable grasp planner for high-dof grippers,” arXiv preprint arXiv:2002.01530 , 2020

Original

2020

Earlier work this paper cites.

J. Ho, A. Jain, and P. Abbeel, “Denoising diffusion probabilistic models,” Advances in neural information processing systems , vol. 33, pp. 6840–6851, 2020

2020

Cited alongside, same era.

T. Liu, Z. Liu, Z. Jiao, Y. Zhu, and S.-C. Zhu, “Synthesizing diverse and physically stable grasps with arbitrary hand structures using differentiable force closure estimator,” IEEE Robotics and Automation Letters , vol. 7, no. 1, pp. 470–477, 2021

2021

Cited alongside, same era.

H. Jiang, S. Liu, J. Wang, and X. Wang, “Hand-object contact consistency reasoning for human grasps generation,” in Proceedings of the International Conference on Computer Vision , 2021

2021

Cited alongside, same era.

D. Turpin, L. Wang, E. Heiden, Y.-C. Chen, M. Macklin, S. Tsogkas, S. Dickinson, and A. Garg, “Grasp’d: Differentiable contact-rich grasp synthesis for multi-fingered hands,” in European Conference on Computer Vision . Springer, 2022, pp. 201–221

2022

Cited alongside, same era.

P. Li, T. Liu, Y. Li, Y. Geng, Y. Zhu, Y. Yang, and S. Huang, “Gendexgrasp: Generalizable dexterous grasping,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 8068–8074

2023

Later among the works it cites.

D. Turpin, T. Zhong, S. Zhang, G. Zhu, J. Liu, R. Singh, E. Heiden, M. Macklin, S. Tsogkas, S. Dickinson, et al. , “Fast-grasp’d: Dexterous multi-finger grasp generation through differentiable simulation,” arXiv preprint arXiv:2306.08132 , 2023

Original

2023

Later among the works it cites.

J. Chen, Y. Chen, J. Zhang, and H. Wang, “Task-oriented dexterous grasp synthesis via differentiable grasp wrench boundary estimator,” arXiv preprint arXiv:2309.13586 , 2023

Original

2023

Later among the works it cites.

Y. Xu, W. Wan, J. Zhang, H. Liu, Z. Shan, H. Shen, R. Wang, H. Geng, Y. Weng, J. Chen, et al. , “Unidexgrasp: Universal robotic dexterous grasping via learning diverse proposal generation and goal-conditioned policy,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 4737–4746