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Robotic grasping is a fundamental aspect of robot functionality, defining how robots interact with objects.
Learning to predict where humans look
Tilke Judd, Krista Ehinger, Frédo Durand, and Antonio Torralba · 2009
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Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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Grasp quality measures: review and performance
Máximo A Roa and Raúl Suárez · 2015
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Physics 101: Learning physical object properties from unlabeled videos
Jiajun Wu, Joseph J Lim, Hongyi Zhang, Joshua B Tenenbaum, and William T Freeman · 2016
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Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, and Ken Goldberg · 2017
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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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What do different evaluation metrics tell us about saliency models?
Zoya Bylinskii, Tilke Judd, Aude Oliva, Antonio Torralba, and Frédo Durand · 2018
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Demo2vec: Reasoning object affordances from online videos
Kuan Fang, Te-Lin Wu, Daniel Yang, Silvio Savarese, and Joseph J Lim · 2018
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Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
Alex Kendall, Yarin Gal, and Roberto Cipolla · 2018
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Toward robotic manipulation
Matthew T Mason · 2018
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Trends and challenges in robot manipulation
Aude Billard and Danica Kragic · 2019
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Pybullet, a python module for physics simulation for games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2019
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Reasoning about physical interactions with object-oriented prediction and planning
Michael Janner, Sergey Levine, William T. Freeman, Joshua B. Tenenbaum, Chelsea Finn, and Jiajun Wu · 2019
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Learning ambidextrous robot grasping policies
Jeffrey Mahler, Matthew Matl, Vishal Satish, Michael Danielczuk, Bill DeRose, Stephen McKinley, and Ken Goldberg · 2019
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Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding
Kaichun Mo, Shilin Zhu, Angel X Chang, Li Yi, Subarna Tripathi, Leonidas J Guibas, and Hao Su · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Densephysnet: Learning dense physical object representations via multi-step dynamic interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng, Joshua B Tenenbaum, and Shuran Song · 2019
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Graspnet-1billion: A large-scale benchmark for general object grasping
Hao-Shu Fang, Chenxi Wang, Minghao Gou, and Cewu Lu · 2020
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Visual grounding of learned physical models
Yunzhu Li, Toru Lin, Kexin Yi, Daniel Bear, Daniel L.K. Yamins, Jiajun Wu, Joshua B. Tenenbaum, and Antonio Torralba · 2020
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Learning long-term visual dynamics with region proposal interaction networks
Haozhi Qi, Xiaolong Wang, Deepak Pathak, Yi Ma, and Jitendra Malik · 2020
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Physion: Evaluating physical prediction from vision in humans and machines
Daniel M Bear, Elias Wang, Damian Mrowca, Felix J Binder, Hsiao-Yu Fish Tung, RT Pramod, Cameron Holdaway, Sirui Tao, Kevin Smith, Fan-Yun Sun, et al · 2021
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Volumetric grasping network: Real-time 6 dof grasp detection in clutter
Michel Breyer, Jen Jen Chung, Lionel Ott, Roland Siegwart, and Juan Nieto · 2021
Cited alongside, same era.
Toward next-generation learned robot manipulation
Jinda Cui and Jeff Trinkle · 2021
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Dynamic visual reasoning by learning differentiable physics models from video and language
Mingyu Ding, Zhenfang Chen, Tao Du, Ping Luo, Josh Tenenbaum, and Chuang Gan · 2021
Cited alongside, same era.
Synergies between affordance and geometry: 6-dof grasp detection via implicit representations
Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, and Yuke Zhu · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, A. Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
Cited alongside, same era.
Visual language maps for robot navigation
Chenguang Huang, Oier Mees, Andy Zeng, and Wolfram Burgard · 2023
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Lisa: Reasoning segmentation via large language model
Xin Lai, Zhuotao Tian, Yukang Chen, Yanwei Li, Yuhui Yuan, Shu Liu, and Jiaya Jia · 2023
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Code as Policies: Language model programs for embodied control
Jacky Liang, Wenlong Huang, Fei Xia, Peng Xu, Karol Hausman, Brian Ichter, Pete Florence, and Andy Zeng · 2023
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Embodiedgpt: Vision-language pre-training via embodied chain of thought
Yao Mu, Qinglong Zhang, Mengkang Hu, Wenhai Wang, Mingyu Ding, Jun Jin, Bin Wang, Jifeng Dai, Yu Qiao, and Ping Luo · 2023
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Chatgpt: Generative pre-trained transformer for conversational agents
OpenAI · 2023
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6-dof contrastive grasp proposal network
Xinghao Zhu, Lingfeng Sun, Yongxiang Fan, and Masayoshi Tomizuka · 2021
Cited alongside, same era.
Do as i can and not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan, and Andy Zeng · 2022
Cited alongside, same era.
Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
Cited alongside, same era.
Rt-1: Robotics transformer for real-world control at scale
Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Jasmine Hsu, et al · 2022
Cited alongside, same era.
Pointnext: Revisiting pointnet++ with improved training and scaling strategies
Guocheng Qian, Yuchen Li, Houwen Peng, Jinjie Mai, Hasan Hammoud, Mohamed Elhoseiny, and Bernard Ghanem · 2022
Cited alongside, same era.
Planning with large language models via corrective re-prompting
Shreyas Sundara Raman, Vanya Cohen, Eric Rosen, Ifrah Idrees, David Paulius, and Stefanie Tellex · 2022
Cited alongside, same era.
Socratic models: Composing zero-shot multimodal reasoning with language
Andy Zeng, Maria Attarian, Brian Ichter, Krzysztof Choromanski, Adrian Wong, Stefan Welker, Federico Tombari, Aveek Purohit, Michael Ryoo, Vikas Sindhwani, et al · 2022
Cited alongside, same era.
Gpt-4 technical report, 2023
OpenAI · 2023
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Open x-embodiment: Robotic learning datasets and rt-x models
Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alex Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anikait Singh, Anthony Brohan, et al · 2023
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ProgPrompt: Generating situated robot task plans using large language models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, and Animesh Garg · 2023
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Llm-planner: Few-shot grounded planning for embodied agents with large language models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su · 2023
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Generative pretraining in multimodality
Quan Sun, Qiying Yu, Yufeng Cui, Fan Zhang, Xiaosong Zhang, Yueze Wang, Hongcheng Gao, Jingjing Liu, Tiejun Huang, and Xinlong Wang · 2023
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Chatgpt for robotics: Design principles and model abilities
Sai Vemprala, Rogerio Bonatti, Arthur Bucker, and Ashish Kapoor · 2023
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Next-gpt: Any-to-any multimodal llm
Shengqiong Wu, Hao Fei, Leigang Qu, Wei Ji, and Tat-Seng Chua · 2023
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mplug-docowl: Modularized multimodal large language model for document understanding, 2023
Jiabo Ye, Anwen Hu, Haiyang Xu, Qinghao Ye, Ming Yan, Yuhao Dan, Chenlin Zhao, Guohai Xu, Chenliang Li, Junfeng Tian, Qian Qi, Ji Zhang, and Fei Huang · 2023
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Gamma: Generalizable articulation modeling and manipulation for articulated objects
Qiaojun Yu, Junbo Wang, Wenhai Liu, Ce Hao, Liu Liu, Lin Shao, Weiming Wang, and Cewu Lu · 2023
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Plan4mc: Skill reinforcement learning and planning for open-world minecraft tasks
Haoqi Yuan, Chi Zhang, Hongcheng Wang, Feiyang Xie, Penglin Cai, Hao Dong, and Zongqing Lu · 2023
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Generalizable long-horizon manipulations with large language models
Haoyu Zhou, Mingyu Ding, Weikun Peng, Masayoshi Tomizuka, Lin Shao, and Chuang Gan · 2023
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Interfacing foundation models’ embeddings
Xueyan Zou, Linjie Li, Jianfeng Wang, Jianwei Yang, Mingyu Ding, Zhengyuan Yang, Feng Li, Hao Zhang, Shilong Liu, Arul Aravinthan, et al · 2023
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Yuanchen Ju, Kaizhe Hu, Guowei Zhang, Gu Zhang, Mingrun Jiang, and Huazhe Xu · 2024
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Ok-robot: What really matters in integrating open-knowledge models for robotics
Peiqi Liu, Yaswanth Orru, Chris Paxton, Nur Muhammad Mahi Shafiullah, and Lerrel Pinto · 2024
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Physion++: Evaluating physical scene understanding that requires online inference of different physical properties
Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Josh Tenenbaum, Dan Yamins, Judith Fan, and Kevin Smith · 2024
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