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Nonprehensile manipulation is crucial for handling objects that are too thin, large, or otherwise ungraspable in unstructured environments.
Progress in nonprehensile manipulation
Matthew T Mason · 1999
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Andrew Y Ng, Daishi Harada, and Stuart Russell · 1999
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Samuel R Buss · 2004
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A reduction of imitation learning and structured prediction to no-regret online learning
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A direct method for trajectory optimization of rigid bodies through contact
Michael Posa, Cecilia Cantu, and Russ Tedrake · 2014
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Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Robust execution of contact-rich motion plans by hybrid force-velocity control
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Yue Ma, Yali Wang, Yue Wu, Ziyu Lyu, Siran Chen, Xiu Li, and Yu Qiao · 2022
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Non-prehensile planar manipulation via trajectory optimization with complementarity constraints
João Moura, Theodoros Stouraitis, and Sethu Vijayakumar · 2022
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Cheng Chi, Zhenjia Xu, Siyuan Feng, Eric Cousineau, Yilun Du, Benjamin Burchfiel, Russ Tedrake, and Shuran Song · 2023
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Pre-and post-contact policy decomposition for non-prehensile manipulation with zero-shot sim-to-real transfer
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Learning preconditions of hybrid force-velocity controllers for contact-rich manipulation
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Yue Ma, Xiaodong Cun, Yingqing He, Chenyang Qi, Xintao Wang, Ying Shan, Xiu Li, and Qifeng Chen · 2023
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Ruicheng Wang, Jialiang Zhang, Jiayi Chen, Yinzhen Xu, Puhao Li, Tengyu Liu, and He Wang · 2023
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Sofar: Language-grounded orientation bridges spatial reasoning and object manipulation
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Unified world models: Coupling video and action diffusion for pretraining on large robotic datasets
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