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Real-world tasks such as garment manipulation and table rearrangement demand robots to perform generalizable, highly precise, and long-horizon actions.
Svo: Fast semi-direct monocular visual odometry
Christian Forster, Matia Pizzoli, and Davide Scaramuzza · 2014
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Orb-slam: a versatile and accurate monocular slam system
Raul Mur-Artal, Jose Maria Martinez Montiel, and Juan D Tardos · 2015
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End-to-end training of deep visuomotor policies
Sergey Levine, Chelsea Finn, Trevor Darrell, and Pieter Abbeel · 2016
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End-to-end learning of driving models from large-scale video datasets
Huazhe Xu, Yang Gao, Fisher Yu, and Trevor Darrell · 2017
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Behavioral cloning from observation
Faraz Torabi, Garrett Warnell, and Peter Stone · 2018
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Self-supervised correspondence in visuomotor policy learning
Peter Florence, Lucas Manuelli, and Russ Tedrake · 2019
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kpam: Keypoint affordances for category-level robotic manipulation
Lucas Manuelli, Wei Gao, Peter Florence, and Russ Tedrake · 2019
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Learning agile robotic locomotion skills by imitating animals
Xue Bin Peng, Erwin Coumans, Tingnan Zhang, Tsang-Wei Lee, Jie Tan, and Sergey Levine · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, and Sergey Levine · 2020
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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State-only imitation learning for dexterous manipulation
Ilija Radosavovic, Xiaolong Wang, Lerrel Pinto, and Jitendra Malik · 2021
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Flowbot3d: Learning 3d articulation flow to manipulate articulated objects
Ben Eisner, Harry Zhang, and David Held · 2022
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Implicit behavioral cloning
Pete Florence, Corey Lynch, Andy Zeng, Oscar A Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, and Jonathan Tompson · 2022
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R3m: A universal visual representation for robot manipulation
Suraj Nair, Aravind Rajeswaran, Vikash Kumar, Chelsea Finn, and Abhinav Gupta · 2022
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Fabricflownet: Bimanual cloth manipulation with a flow-based policy
Thomas Weng, Sujay Man Bajracharya, Yufei Wang, Khush Agrawal, and David Held · 2022
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Dexart: Benchmarking generalizable dexterous manipulation with articulated objects
Chen Bao, Helin Xu, Yuzhe Qin, and Xiaolong Wang · 2023
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Visual dexterity: In-hand reorientation of novel and complex object shapes
Tao Chen, Megha Tippur, Siyang Wu, Vikash Kumar, Edward Adelson, and Pulkit Agrawal · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Zhenjia Xu, Siyuan Feng, Eric Cousineau, Yilun Du, Benjamin Burchfiel, Russ Tedrake, and Shuran Song · 2023
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Act3d: 3d feature field transformers for multi-task robotic manipulation
Theophile Gervet, Zhou Xian, Nikolaos Gkanatsios, and Katerina Fragkiadaki · 2023
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Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Dinov2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, et al · 2023
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Toolflownet: Robotic manipulation with tools via predicting tool flow from point clouds
Daniel Seita, Yufei Wang, Sarthak J Shetty, Edward Yao Li, Zackory Erickson, and David Held · 2023
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Masked world models for visual control
Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, and Pieter Abbeel · 2023
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Droid: A large-scale in-the-wild robot manipulation dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, et al · 2024
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Openvla: An open-source vision-language-action model
Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Foster, Grace Lam, Pannag Sanketi, et al · 2024
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P3-po: Prescriptive point priors for visuo-spatial generalization of robot policies
Mara Levy, Siddhant Haldar, Lerrel Pinto, and Abhinav Shirivastava · 2024
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Data scaling laws in imitation learning for robotic manipulation
Fanqi Lin, Yingdong Hu, Pingyue Sheng, Chuan Wen, Jiacheng You, and Yang Gao · 2024
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Perceiver-actor: A multi-task transformer for robotic manipulation
Mohit Shridhar, Lucas Manuelli, and Dieter Fox · 2023
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Emergent correspondence from image diffusion
Luming Tang, Menglin Jia, Qianqian Wang, Cheng Perng Phoo, and Bharath Hariharan · 2023
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Any-point trajectory modeling for policy learning
Chuan Wen, Xingyu Lin, John So, Kai Chen, Qi Dou, Yang Gao, and Pieter Abbeel · 2023
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Useek: Unsupervised se (3)-equivariant 3d keypoints for generalizable manipulation
Zhengrong Xue, Zhecheng Yuan, Jiashun Wang, Xueqian Wang, Yang Gao, and Huazhe Xu · 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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H Bharadhwaj, R Mottaghi, A Gupta, and S Tulsiani · 2024
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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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Songming Liu, Lingxuan Wu, Bangguo Li, Hengkai Tan, Huayu Chen, Zhengyi Wang, Ke Xu, Hang Su, and Jun Zhu · 2024
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Task-oriented hierarchical object decomposition for visuomotor control
Jianing Qian, Yunshuang Li, Bernadette Bucher, and Dinesh Jayaraman · 2024
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Am-radio: Agglomerative vision foundation model reduce all domains into one
Mike Ranzinger, Greg Heinrich, Jan Kautz, and Pavlo Molchanov · 2024
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Composing pre-trained object-centric representations for robotics from” what” and” where” foundation models
Junyao Shi, Jianing Qian, Yecheng Jason Ma, and Dinesh Jayaraman · 2024
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Robotap: Tracking arbitrary points for few-shot visual imitation
Mel Vecerik, Carl Doersch, Yi Yang, Todor Davchev, Yusuf Aytar, Guangyao Zhou, Raia Hadsell, Lourdes Agapito, and Jon Scholz · 2024
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Instant policy: In-context imitation learning via graph diffusion
Vitalis Vosylius and Edward Johns · 2024
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Flow as the cross-domain manipulation interface
Mengda Xu, Zhenjia Xu, Yinghao Xu, Cheng Chi, Gordon Wetzstein, Manuela Veloso, and Shuran Song · 2024
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Equibot: Sim (3)-equivariant diffusion policy for generalizable and data efficient learning
Jingyun Yang, Zi-ang Cao, Congyue Deng, Rika Antonova, Shuran Song, and Jeannette Bohg · 2024
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General flow as foundation affordance for scalable robot learning
Chengbo Yuan, Chuan Wen, Tong Zhang, and Yang Gao · 2024
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A survey of imitation learning: Algorithms, recent developments, and challenges
Maryam Zare, Parham M Kebria, Abbas Khosravi, and Saeid Nahavandi · 2024
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Yanjie Ze, Gu Zhang, Kangning Zhang, Chenyuan Hu, Muhan Wang, and Huazhe Xu · 2024
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Leveraging locality to boost sample efficiency in robotic manipulation
Tong Zhang, Yingdong Hu, Jiacheng You, and Yang Gao · 2024
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Aloha unleashed: A simple recipe for robot dexterity
Tony Z Zhao, Jonathan Tompson, Danny Driess, Pete Florence, Kamyar Ghasemipour, Chelsea Finn, and Ayzaan Wahid · 2024
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Robo-abc: Affordance generalization beyond categories via semantic correspondence for robot manipulation
Yuanchen Ju, Kaizhe Hu, Guowei Zhang, Gu Zhang, Mingrun Jiang, and Huazhe Xu · 2025
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Cotracker: It is better to track together
Nikita Karaev, Ignacio Rocco, Benjamin Graham, Natalia Neverova, Andrea Vedaldi, and Christian Rupprecht · 2025
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