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The deep learning models has significantly advanced dexterous manipulation techniques for multi-fingered hand grasping.
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2023
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2023
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Cited alongside, same era.
M. Corsaro, S. Tellex, and G. Konidaris, “Learning to detect multi-modal grasps for dexterous grasping in dense clutter,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2021, pp. 4647–4653
2021
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2021
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2021
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J. Lundell, E. Corona, T. N. Le, F. Verdoja, P. Weinzaepfel, G. Rogez, F. Moreno-Noguer, and V. Kyrki, “Multi-fingan: Generative coarse-to-fine sampling of multi-finger grasps,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. 4495–4501
2021
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T. Zhu, R. Wu, X. Lin, and Y. Sun, “Toward human-like grasp: Dexterous grasping via semantic representation of object-hand,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 15 741–15 751
2021
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2021
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Y. Li, W. Wei, D. Li, P. Wang, W. Li, and J. Zhong, “Hgc-net: Deep anthropomorphic hand grasping in clutter,” in 2022 International Conference on Robotics and Automation (ICRA) . IEEE, 2022, pp. 714–720
2022
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H. Duan, P. Wang, Y. Li, D. Li, and W. Wei, “Learning human-to-robot dexterous handovers for anthropomorphic hand,” IEEE Transactions on Cognitive and Developmental Systems , vol. 15, no. 3, pp. 1224–1238, 2022
2022
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R. Wang, J. Zhang, J. Chen, Y. Xu, P. Li, T. Liu, and H. Wang, “Dexgraspnet: A large-scale robotic dexterous grasp dataset for general objects based on simulation,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 11 359–11 366
2023
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Q. Liu, Y. Cui, Q. Ye, Z. Sun, H. Li, G. Li, L. Shao, and J. Chen, “Dexrepnet: Learning dexterous robotic grasping network with geometric and spatial hand-object representations,” in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2023, pp. 3153–3160
2023
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Z. Chen, F. Long, Z. Qiu, T. Yao, W. Zhou, J. Luo, and T. Mei, “Anchorformer: Point cloud completion from discriminative nodes,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2023, pp. 13 581–13 590
2023
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J. Jian, X. Liu, M. Li, R. Hu, and J. Liu, “Affordpose: A large-scale dataset of hand-object interactions with affordance-driven hand pose,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 14 713–14 724
2023
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2023
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H. Duan, Y. Li, D. Li, W. Wei, Y. Huang, and P. Wang, “Learning realistic and reasonable grasps for anthropomorphic hand in cluttered scenes,” in 2024 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2024, pp. 1893–1899
2024
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J. Zhang, H. Liu, D. Li, X. Yu, H. Geng, Y. Ding, J. Chen, and H. Wang, “Dexgraspnet 2.0: Learning generative dexterous grasping in large-scale synthetic cluttered scenes,” in 8th Annual Conference on Robot Learning , 2024
2024
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2024
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2024
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2024
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2024
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K. Zakka, “Mink,” 2024. [Online]. Available: https://github.com/kevinzakka/mink
2024
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2050
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