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Generating large-scale demonstrations for dexterous hand manipulation remains challenging, and several approaches have been proposed in recent years to address this.
Planning optimal grasps
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On characterizing and computing three-and four-finger force-closure grasps of polyhedral objects
Jean Ponce, Steve Sullivan, J-D Boissonnat, and J-P Merlet · 1993
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On computing four-finger equilibrium and force-closure grasps of polyhedral objects
Jean Ponce, Steve Sullivan, Attawith Sudsang, Jean-Daniel Boissonnat, and Jean-Pierre Merlet · 1997
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Shadow hand, 2005
Shadow Robot Company · 2005
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Distance between a point and a convex cone in n n -dimensional space: Computation and applications
Yu Zheng and Chee-Meng Chew · 2009
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On the manipulability ellipsoids of underactuated robotic hands with compliance
Domenico Prattichizzo, Monica Malvezzi, Marco Gabiccini, and Antonio Bicchi · 2012
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From caging to grasping
Alberto Rodriguez, Matthew T Mason, and Steve Ferry · 2012
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On the synthesis of feasible and prehensile robotic grasps
Carlos Rosales, Raúl Suárez, Marco Gabiccini, and Antonio Bicchi · 2012
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Synthesis and optimization of force closure grasps via sequential semidefinite programming
Hongkai Dai, Anirudha Majumdar, and Russ Tedrake · 2018
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Learning joint reconstruction of hands and manipulated objects
Yana Hasson, Gul Varol, Dimitrios Tzionas, Igor Kalevatykh, Michael J Black, Ivan Laptev, and Cordelia Schmid · 2019
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Learning dexterous in-hand manipulation
OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, et al · 2020
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Contactpose: A dataset of grasps with object contact and hand pose
Samarth Brahmbhatt, Chengcheng Tang, Christopher D Twigg, Charles C Kemp, and James Hays · 2020
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Ganhand: Predicting human grasp affordances in multi-object scenes
Enric Corona, Albert Pumarola, Guillem Alenya, Francesc Moreno-Noguer, and Grégory Rogez · 2020
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Honnotate: A method for 3d annotation of hand and object poses
Shreyas Hampali, Mahdi Rad, Markus Oberweger, and Vincent Lepetit · 2020
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Deep differentiable grasp planner for high-dof grippers
Min Liu, Zherong Pan, Kai Xu, Kanishka Ganguly, and Dinesh Manocha · 2020
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Multi-fingered active grasp learning
Qingkai Lu, Mark Van der Merwe, and Tucker Hermans · 2020
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Deep dynamics models for learning dexterous manipulation
Anusha Nagabandi, Kurt Konolige, Sergey Levine, and Vikash Kumar · 2020
Cited alongside, same era.
Unigrasp: Learning a unified model to grasp with multifingered robotic hands
Lin Shao, Fabio Ferreira, Mikael Jorda, Varun Nambiar, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Oussama Khatib, and Jeannette Bohg · 2020
Cited alongside, same era.
Sapien: A simulated part-based interactive environment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, et al · 2020
Cited alongside, same era.
Dexycb: A benchmark for capturing hand grasping of objects
Yu-Wei Chao, Wei Yang, Yu Xiang, Pavlo Molchanov, Ankur Handa, Jonathan Tremblay, Yashraj S Narang, Karl Van Wyk, Umar Iqbal, Stan Birchfield, et al · 2021
Cited alongside, same era.
Synthesizing diverse and physically stable grasps with arbitrary hand structures using differentiable force closure estimator
Tengyu Liu, Zeyu Liu, Ziyuan Jiao, Yixin Zhu, and Song-Chun Zhu · 2021
Cited alongside, same era.
Fast-grasp’d: Dexterous multi-finger grasp generation through differentiable simulation
Dylan Turpin, Tao Zhong, Shutong Zhang, Guanglei Zhu, Eric Heiden, Miles Macklin, Stavros Tsogkas, Sven Dickinson, and Animesh Garg · 2023
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Dexgraspnet: A large-scale robotic dexterous grasp dataset for general objects based on simulation
Ruicheng Wang, Jialiang Zhang, Jiayi Chen, Yinzhen Xu, Puhao Li, Tengyu Liu, and He Wang · 2023
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Unidexgrasp: Universal robotic dexterous grasping via learning diverse proposal generation and goal-conditioned policy
Yinzhen Xu, Weikang Wan, Jialiang Zhang, Haoran Liu, Zikang Shan, Hao Shen, Ruicheng Wang, Haoran Geng, Yijia Weng, Jiayi Chen, et al · 2023
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Learning continuous grasping function with a dexterous hand from human demonstrations
Jianglong Ye, Jiashun Wang, Binghao Huang, Yuzhe Qin, and Xiaolong Wang · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z. Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
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Ddgc: Generative deep dexterous grasping in clutter
Jens Lundell, Francesco Verdoja, and Ville Kyrki · 2021
Cited alongside, same era.
Isaac gym: High performance gpu-based physics simulation for robot learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, et al · 2021
Cited alongside, same era.
Cpf: Learning a contact potential field to model the hand-object interaction
Lixin Yang, Xinyu Zhan, Kailin Li, Wenqiang Xu, Jiefeng Li, and Cewu Lu · 2021
Cited alongside, same era.
Dextransfer: Real world multi-fingered dexterous grasping with minimal human demonstrations
Zoey Qiuyu Chen, Karl Van Wyk, Yu-Wei Chao, Wei Yang, Arsalan Mousavian, Abhishek Gupta, and Dieter Fox · 2022
Cited alongside, same era.
Warp: A high-performance python framework for gpu simulation and graphics
Miles Macklin · 2022
Cited alongside, same era.
Dexmv: Imitation learning for dexterous manipulation from human videos
Yuzhe Qin, Yueh-Hua Wu, Shaowei Liu, Hanwen Jiang, Ruihan Yang, Yang Fu, and Xiaolong Wang · 2022
Cited alongside, same era.
Grasp’d: Differentiable contact-rich grasp synthesis for multi-fingered hands
Dylan Turpin, Liquan Wang, Eric Heiden, Yun-Chun Chen, Miles Macklin, Stavros Tsogkas, Sven Dickinson, and Animesh Garg · 2022
Cited alongside, same era.
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π 0 \pi 0 : A vision-language-action flow model for general robot control
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, et al · 2024
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Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots
Cheng Chi, Zhenjia Xu, Chuer Pan, Eric Cousineau, Benjamin Burchfiel, Siyuan Feng, Russ Tedrake, and Shuran Song · 2024
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Synh2r: Synthesizing hand-object motions for learning human-to-robot handovers
Sammy Christen, Lan Feng, Wei Yang, Yu-Wei Chao, Otmar Hilliges, and Jie Song · 2024
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Mobile aloha: Learning bimanual mobile manipulation with low-cost whole-body teleoperation
Zipeng Fu, Tony Z. Zhao, and Chelsea Finn · 2024
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Realdex: Towards human-like grasping for robotic dexterous hand
Yumeng Liu, Yaxun Yang, Youzhuo Wang, Xiaofei Wu, Jiamin Wang, Yichen Yao, Sören Schwertfeger, Sibei Yang, Wenping Wang, Jingyi Yu, Xuming He, and Yuexin Ma · 2024
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Ugg: Unified generative grasping
Jiaxin Lu, Hao Kang, Haoxiang Li, Bo Liu, Yiding Yang, Qixing Huang, and Gang Hua · 2024
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Dextrah-g: Pixels-to-action dexterous arm-hand grasping with geometric fabrics
Tyler Ga Wei Lum, Martin Matak, Viktor Makoviychuk, Ankur Handa, Arthur Allshire, Tucker Hermans, Nathan D. Ratliff, and Karl Van Wyk · 2024
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Dextrah-rgb: Visuomotor policies to grasp anything with dexterous hands
Ritvik Singh, Arthur Allshire, Ankur Handa, Nathan Ratliff, and Karl Van Wyk · 2024
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Maniskill3: Gpu parallelized robotics simulation and rendering for generalizable embodied ai
Stone Tao, Fanbo Xiang, Arth Shukla, Yuzhe Qin, Xander Hinrichsen, Xiaodi Yuan, Chen Bao, Xinsong Lin, Yulin Liu, Tse kai Chan, Yuan Gao, Xuanlin Li, Tongzhou Mu, Nan Xiao, Arnav Gurha, Zhiao Huang, Roberto Calandra, Rui Chen, Shan Luo, and Hao Su · 2024
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Dexdiffuser: Generating dexterous grasps with diffusion models
Zehang Weng, Haofei Lu, Danica Kragic, and Jens Lundell · 2024
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Dexgraspnet 2.0: Learning generative dexterous grasping in large-scale synthetic cluttered scenes
Jialiang Zhang, Haoran Liu, Danshi Li, XinQiang Yu, Haoran Geng, Yufei Ding, Jiayi Chen, and He Wang · 2024
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