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Enabling robots to learn novel tasks in a data-efficient manner is a long-standing challenge.
Integration of paths–a faithful representation of paths by noncommutative formal power series
Kuo-Tsai Chen · 1958
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Continual learning in reinforcement environments
Mark Bishop Ring · 1994
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Sparse multi-task reinforcement learning
Daniele Calandriello, Alessandro Lazaric, and Marcello Restelli · 2014
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Learning shared representations in multi-task reinforcement learning
Diana Borsa, Thore Graepel, and John Shawe-Taylor · 2016
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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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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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Learning an embedding space for transferable robot skills
Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, and Martin Riedmiller · 2018
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Task-embedded control networks for few-shot imitation learning
Stephen James, Michael Bloesch, and Andrew J Davison · 2018
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Self-imitation learning
Junhyuk Oh, Yijie Guo, Satinder Singh, and Honglak Lee · 2018
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Reinforced continual learning
Ju Xu and Zhanxing Zhu · 2018
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Reinforcement learning: Theory and algorithms
Alekh Agarwal, Nan Jiang, Sham M Kakade, and Wen Sun · 2019
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Deep signature transforms
Patrick Kidger, Patric Bonnier, Imanol Perez Arribas, Cristopher Salvi, and Terry Lyons · 2019
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Efficient off-policy meta-reinforcement learning via probabilistic context variables
Kate Rakelly, Aurick Zhou, Chelsea Finn, Sergey Levine, and Deirdre Quillen · 2019
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Dynamics-aware unsupervised discovery of skills
Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, and Karol Hausman · 2019
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Transfer of samples in policy search via multiple importance sampling
Andrea Tirinzoni, Mattia Salvini, and Marcello Restelli · 2019
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Variable compliance control for robotic peg-in-hole assembly: A deep-reinforcement-learning approach
Cristian C. Beltran-Hernandez, Damien Petit, Ixchel G. Ramirez-Alpizar, and Kensuke Harada · 2020
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Benchmarking protocols for evaluating small parts robotic assembly systems
Kenneth Kimble, Karl Van Wyk, Joe Falco, Elena Messina, Yu Sun, Mizuho Shibata, Wataru Uemura, and Yasuyoshi Yokokohji · 2020
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Context-aware dynamics model for generalization in model-based reinforcement learning
Kimin Lee, Younggyo Seo, Seunghyun Lee, Honglak Lee, and Jinwoo Shin · 2020
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Learning latent plans from play
Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, and Pierre Sermanet · 2020
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Self-imitation learning via generalized lower bound q-learning
Yunhao Tang · 2020
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Bridge data: Boosting generalization of robotic skills with cross-domain datasets
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, and Sergey Levine · 2021
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Adarl: What, where, and how to adapt in transfer reinforcement learning
Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, and Kun Zhang · 2021
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Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Wenzhao Lian, Chang Su, Mel Vecerik, Ning Ye, Stefan Schaal, and Jon Scholz · 2021
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Maniskill: Generalizable manipulation skill benchmark with large-scale demonstrations
Tongzhou Mu, Zhan Ling, Fanbo Xiang, Derek Yang, Xuanlin Li, Stone Tao, Zhiao Huang, Zhiwei Jia, and Hao Su · 2021
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Masked visual pre-training for motor control
Tete Xiao, Ilija Radosavovic, Trevor Darrell, and Jitendra Malik · 2022
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Offline meta-reinforcement learning for industrial insertion
Tony Z Zhao, Jianlan Luo, Oleg Sushkov, Rugile Pevceviciute, Nicolas Heess, Jon Scholz, Stefan Schaal, and Sergey Levine · 2022
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Behavior retrieval: Few-shot imitation learning by querying unlabeled datasets
Maximilian Du, Suraj Nair, Dorsa Sadigh, and Chelsea Finn · 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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Industreal: Transferring contact-rich assembly tasks from simulation to reality
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Accelerating reinforcement learning with learned skill priors
Karl Pertsch, Youngwoon Lee, and Joseph Lim · 2021
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Concept2robot: Learning manipulation concepts from instructions and human demonstrations
Lin Shao, Toki Migimatsu, Qiang Zhang, Karen Yang, and Jeannette Bohg · 2021
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Multi-task reinforcement learning with context-based representations
Shagun Sodhani, Amy Zhang, and Joelle Pineau · 2021
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Insertionnet-a scalable solution for insertion
Oren Spector and Dotan Di Castro · 2021
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6d robotic assembly based on rgb-only object pose estimation
Bowen Fu, Sek Kun Leong, Xiaocong Lian, and Xiangyang Ji · 2022
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Learning action translator for meta reinforcement learning on sparse-reward tasks
Yijie Guo, Qiucheng Wu, and Honglak Lee · 2022
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Bc-z: Zero-shot task generalization with robotic imitation learning
Eric Jang, Alex Irpan, Mohi Khansari, Daniel Kappler, Frederik Ebert, Corey Lynch, Sergey Levine, and Chelsea Finn · 2022
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Performance measures to benchmark the grasping, manipulation, and assembly of deformable objects typical to manufacturing applications
Kenneth Kimble, Justin Albrecht, Megan Zimmerman, and Joe Falco · 2022
Cited alongside, same era.
Bingjie Tang, Michael A Lin, Iretiayo Akinola, Ankur Handa, Gaurav S Sukhatme, Fabio Ramos, Dieter Fox, and Yashraj Narang · 2023
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Unidexgrasp++: Improving dexterous grasping policy learning via geometry-aware curriculum and iterative generalist-specialist learning
Weikang Wan, Haoran Geng, Yun Liu, Zikang Shan, Yaodong Yang, Li Yi, and He Wang · 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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Efficient sim-to-real transfer of contact-rich manipulation skills with online admittance residual learning
Xiang Zhang, Changhao Wang, Lingfeng Sun, Zheng Wu, Xinghao Zhu, and Masayoshi Tomizuka · 2023
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A definition of continual reinforcement learning
David Abel, André Barreto, Benjamin Van Roy, Doina Precup, Hado P van Hasselt, and Satinder Singh · 2024
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Path signatures for diversity in probabilistic trajectory optimisation
Lucas Barcelos, Tin Lai, Rafael Oliveira, Paulo Borges, and Fabio Ramos · 2024
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Rt-h: Action hierarchies using language
Suneel Belkhale, Tianli Ding, Ted Xiao, Pierre Sermanet, Quon Vuong, Jonathan Tompson, Yevgen Chebotar, Debidatta Dwibedi, and Dorsa Sadigh · 2024
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Rvt-2: Learning precise manipulation from few demonstrations
Ankit Goyal, Valts Blukis, Jie Xu, Yijie Guo, Yu-Wei Chao, and Dieter Fox · 2024
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Ram: Retrieval-based affordance transfer for generalizable zero-shot robotic manipulation
Yuxuan Kuang, Junjie Ye, Haoran Geng, Jiageng Mao, Congyue Deng, Leonidas Guibas, He Wang, and Yue Wang · 2024
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Flowretrieval: Flow-guided data retrieval for few-shot imitation learning
Li-Heng Lin, Yuchen Cui, Amber Xie, Tianyu Hua, and Dorsa Sadigh · 2024
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Forge: Force-guided exploration for robust contact-rich manipulation under uncertainty
Michael Noseworthy, Bingjie Tang, Bowen Wen, Ankur Handa, Nicholas Roy, Dieter Fox, Fabio Ramos, Yashraj Narang, and Iretiayo Akinola · 2024
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Automate: Specialist and generalist assembly policies over diverse geometries
Bingjie Tang, Iretiayo Akinola, Jie Xu, Bowen Wen, Ankur Handa, Karl Van Wyk, Dieter Fox, Gaurav S Sukhatme, Fabio Ramos, and Yashraj Narang · 2024
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Asap: automated sequence planning for complex robotic assembly with physical feasibility
Yunsheng Tian, Karl DD Willis, Bassel Al Omari, Jieliang Luo, Pingchuan Ma, Yichen Li, Farhad Javid, Edward Gu, Joshua Jacob, Shinjiro Sueda, et al · 2024
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Poliformer: Scaling on-policy rl with transformers results in masterful navigators
Kuo-Hao Zeng, Zichen Zhang, Kiana Ehsani, Rose Hendrix, Jordi Salvador, Alvaro Herrasti, Ross Girshick, Aniruddha Kembhavi, and Luca Weihs · 2024
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Distilling and retrieving generalizable knowledge for robot manipulation via language corrections
Lihan Zha, Yuchen Cui, Li-Heng Lin, Minae Kwon, Montserrat Gonzalez Arenas, Andy Zeng, Fei Xia, and Dorsa Sadigh · 2024
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Retrieval-augmented embodied agents
Yichen Zhu, Zhicai Ou, Xiaofeng Mou, and Jian Tang · 2024
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