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Dexterous robotic manipulation remains a challenging domain due to its strict demands for precision and robustness on both hardware and software.
Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1988
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Raymond R. Ma and Aaron M. Dollar · 2014
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Raphael Deimel, Marcel Radke, and Oliver Brock · 2016
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Learning dexterous manipulation for a soft robotic hand from human demonstrations
Abhishek Gupta, Clemens Eppner, Sergey Levine, and Pieter Abbeel · 2016
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Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi Chen, Ken Goldberg, and Pieter Abbeel · 2018
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Divye Jain, Andrew Li, Shivam Singhal, Aravind Rajeswaran, Vikash Kumar, and Emanuel Todorov · 2019
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Robel: Robotics benchmarks for learning with low-cost robots
Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, and Vikash Kumar · 2020
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Learning dexterous in-hand manipulation
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Dexpilot: Vision-based teleoperation of dexterous robotic hand-arm system
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A review of robot learning for manipulation: Challenges, representations, and algorithms
Oliver Kroemer, Scott Niekum, and George Konidaris · 2021
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The stewart hand: A highly dexterous, six-degrees-of-freedom manipulator based on the stewart-gough platform
Connor McCann, Vatsal Patel, and Aaron Dollar · 2021
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Insertionnet-a scalable solution for insertion
Oren Spector and Dotan Di Castro · 2021
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Xianyi Cheng, Sarvesh Patil, Zeynep Temel, Oliver Kroemer, and Matthew T Mason · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
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Shadow dexterous hand
Shadow Robot Company · 2023
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Deft: Dexterous fine-tuning for hand policies
Aditya Kannan, Kenneth Shaw, Shikhar Bahl, Pragna Mannam, and Deepak Pathak · 2023
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Learning preconditions of hybrid force-velocity controllers for contact-rich manipulation
Jacky Liang, Xianyi Cheng, and Oliver Kroemer · 2023
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Extrinsic dexterous manipulation with a direct-drive hand: A case study
Arnav Gupta, Yuemin Mao, Ankit Bhatia, Xianyi Cheng, Jonathan King, Yifan Hou, and Matthew T Mason · 2022
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Vision-based manipulators need to also see from their hands
Kyle Hsu, Moo Jin Kim, Rafael Rafailov, Jiajun Wu, and Chelsea Finn · 2022
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2022
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Complex in-hand manipulation via compliance-enabled finger gaiting and multi-modal planning
Andrew S Morgan, Kaiyu Hang, Bowen Wen, Kostas Bekris, and Aaron M Dollar · 2022
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Steffen Puhlmann, Jason Harris, and Oliver Brock · 2022
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From one hand to multiple hands: Imitation learning for dexterous manipulation from single-camera teleoperation
Yuzhe Qin, Hao Su, and Xiaolong Wang · 2022
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Pragna Mannam, Kenneth Shaw, Dominik Bauer, Jean Oh, Deepak Pathak, and Nancy Pollard · 2023
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In-hand cube reconfiguration: Simplified
Sumit Patidar, Adrian Sieler, and Oliver Brock · 2023
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In-hand object rotation via rapid motor adaptation
Haozhi Qi, Ashish Kumar, Roberto Calandra, Yi Ma, and Jitendra Malik · 2023
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Goal-conditioned imitation learning using score-based diffusion policies
Moritz Reuss, Maximilian Li, Xiaogang Jia, and Rudolf Lioutikov · 2023
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Allegro hand
Wonik Robotics · 2023
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Leap hand: Low-cost, efficient, and anthropomorphic hand for robot learning
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Gello: A general, low-cost, and intuitive teleoperation framework for robot manipulators
Philipp Wu, Yide Shentu, Zhongke Yi, Xingyu Lin, and Pieter Abbeel · 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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Learning to grasp the ungraspable with emergent extrinsic dexterity
Wenxuan Zhou and David Held · 2023
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Deltahands: A synergistic dexterous hand framework based on delta robots
Zilin Si, Kevin Zhang, Oliver Kroemer, and F Zeynep Temel · 2024
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