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Grasping in cluttered scenes remains highly challenging for dexterous hands due to the scarcity of data.
Graspit! a versatile simulator for robotic grasping
A. T. Miller and P. K. Allen · 2004
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Shapenet: An information-rich 3d model repository
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Grasp pose detection in point clouds
A. Ten Pas, M. Gualtieri, K. Saenko, and R. Platt · 2017
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Neural ordinary differential equations
R. T. Chen, Y. Rubanova, J. Bettencourt, and D. K. Duvenaud · 2018
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Closing the loop for robotic grasping: A real-time, generative grasp synthesis approach
D. Morrison, P. Corke, and J. Leitner · 2018
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Real-world multiobject, multigrasp detection
F.-J. Chu, R. Xu, and P. A. Vela · 2018
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Synthesis and optimization of force closure grasps via sequential semidefinite programming
H. Dai, A. Majumdar, and R. Tedrake · 2018
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6-dof graspnet: Variational grasp generation for object manipulation
A. Mousavian, C. Eppner, and D. Fox · 2019
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Multi-view picking: Next-best-view reaching for improved grasping in clutter
D. Morrison, P. Corke, and J. Leitner · 2019
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Increasing the generalisaton capacity of conditional vaes
A. Klushyn, N. Chen, B. Cseke, J. Bayer, and P. van der Smagt · 2019
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Pointnetgpd: Detecting grasp configurations from point sets
H. Liang, X. Ma, S. Li, M. Görner, S. Tang, B. Fang, F. Sun, and J. Zhang · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
C. Choy, J. Gwak, and S. Savarese · 2019
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Mish: A self regularized non-monotonic activation function
D. Misra · 2019
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Graspnet-1billion: A large-scale benchmark for general object grasping
H.-S. Fang, C. Wang, M. Gou, and C. Lu · 2020
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Deep differentiable grasp planner for high-dof grippers
M. Liu, Z. Pan, K. Xu, K. Ganguly, and D. Manocha · 2020
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Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
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Score-based generative modeling through stochastic differential equations
Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, and B. Poole · 2020
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An analysis of svd for deep rotation estimation
J. Levinson, C. Esteves, K. Chen, N. Snavely, A. Kanazawa, A. Rostamizadeh, and A. Makadia · 2020
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nflows: normalizing flows in PyTorch, Nov. 2020
C. Durkan, A. Bekasov, I. Murray, and G. Papamakarios · 2020
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Ddgc: Generative deep dexterous grasping in clutter
J. Lundell, F. Verdoja, and V. Kyrki · 2021
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Hand-object contact consistency reasoning for human grasps generation
H. Jiang, S. Liu, J. Wang, and X. Wang · 2021
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Acronym: A large-scale grasp dataset based on simulation
C. Eppner, A. Mousavian, and D. Fox · 2021
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Depthgrasp: Depth completion of transparent objects using self-attentive adversarial network with spectral residual for grasping
Progressive distillation for fast sampling of diffusion models
T. Salimans and J. Ho · 2022
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Domain randomization-enhanced depth simulation and restoration for perceiving and grasping specular and transparent objects
Q. Dai, J. Zhang, Q. Li, T. Wu, H. Dong, Z. Liu, P. Tan, and H. Wang · 2022
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Dexgraspnet: A large-scale robotic dexterous grasp dataset for general objects based on simulation
R. Wang, J. Zhang, J. Chen, Y. Xu, P. Li, T. Liu, and H. Wang · 2023
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Fast-grasp’d: Dexterous multi-finger grasp generation through differentiable simulation, 2023
D. Turpin, T. Zhong, S. Zhang, G. Zhu, J. Liu, R. Singh, E. Heiden, M. Macklin, S. Tsogkas, S. Dickinson, and A. Garg · 2023
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Gendexgrasp: Generalizable dexterous grasping
P. Li, T. Liu, Y. Li, Y. Geng, Y. Zhu, Y. Yang, and S. Huang · 2023
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Y. Tang, J. Chen, Z. Yang, Z. Lin, Q. Li, and W. Liu · 2021
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Graspness discovery in clutters for fast and accurate grasp detection
C. Wang, H.-S. Fang, M. Gou, H. Fang, J. Gao, and C. Lu · 2021
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Volumetric grasping network: Real-time 6 dof grasp detection in clutter, 2021
M. Breyer, J. J. Chung, L. Ott, R. Siegwart, and J. Nieto · 2021
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Synergies between affordance and geometry: 6-dof grasp detection via implicit representations, 2021
Z. Jiang, Y. Zhu, M. Svetlik, K. Fang, and Y. Zhu · 2021
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Contact-graspnet: Efficient 6-dof grasp generation in cluttered scenes
M. Sundermeyer, A. Mousavian, R. Triebel, and D. Fox · 2021
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Synthesizing diverse and physically stable grasps with arbitrary hand structures using differentiable force closure estimator
T. Liu, Z. Liu, Z. Jiao, Y. Zhu, and S.-C. Zhu · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
V. Makoviychuk, L. Wawrzyniak, Y. Guo, M. Lu, K. Storey, M. Macklin, D. Hoeller, N. Rudin, A. Allshire, A. Handa, et al · 2021
Cited alongside, same era.
Unidexgrasp++: Improving dexterous grasping policy learning via geometry-aware curriculum and iterative generalist-specialist learning
W. Wan, H. Geng, Y. Liu, Z. Shan, Y. Yang, L. Yi, and H. Wang · 2023
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Leap hand: Low-cost, efficient, and anthropomorphic hand for robot learning
K. Shaw, A. Agarwal, and D. Pathak · 2023
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Task-oriented dexterous grasp synthesis via differentiable grasp wrench boundary estimator
J. Chen, Y. Chen, J. Zhang, and H. Wang · 2023
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Unidexgrasp: Universal robotic dexterous grasping via learning diverse proposal generation and goal-conditioned policy
Y. Xu, W. Wan, J. Zhang, H. Liu, Z. Shan, H. Shen, R. Wang, H. Geng, Y. Weng, J. Chen, et al · 2023
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Dexterous functional grasping
A. Agarwal, S. Uppal, K. Shaw, and D. Pathak · 2023
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Leap hand: Low-cost, efficient, and anthropomorphic hand for robot learning
K. Shaw, A. Agarwal, and D. Pathak · 2023
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Anygrasp: Robust and efficient grasp perception in spatial and temporal domains
H.-S. Fang, C. Wang, H. Fang, M. Gou, J. Liu, H. Yan, W. Liu, Y. Xie, and C. Lu · 2023
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curobo: Parallelized collision-free minimum-jerk robot motion generation
B. Sundaralingam, S. K. S. Hari, A. Fishman, C. Garrett, K. Van Wyk, V. Blukis, A. Millane, H. Oleynikova, A. Handa, F. Ramos, et al · 2023
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L. Zhang, K. Bai, G. Huang, Z. Chen, and J. Zhang · 2024
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J. Shi, Y. Jin, D. Li, H. Niu, Z. Jin, H. Wang, et al · 2024
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Dexcap: Scalable and portable mocap data collection system for dexterous manipulation, 2024
C. Wang, H. Shi, W. Wang, R. Zhang, L. Fei-Fei, and C. K. Liu · 2024
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