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Building a lifelong robot that can effectively leverage prior knowledge for continuous skill acquisition remains significantly challenging.
Learning and generalization of motor skills by learning from demonstration
Peter Pastor, Heiko Hoffmann, Tamim Asfour, and Stefan Schaal · 2009
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Data-driven grasp synthesis—a survey
Jeannette Bohg, Antonio Morales, Tamim Asfour, and Danica Kragic · 2013
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Dynamical movement primitives: learning attractor models for motor behaviors
Auke Jan Ijspeert, Jun Nakanishi, Heiko Hoffmann, Peter Pastor, and Stefan Schaal · 2013
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A constraint-based method for solving sequential manipulation planning problems
Tomás Lozano-Pérez and Leslie Pack Kaelbling · 2014
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Learning modular policies for robotics
Gerhard Neumann, Christian Daniel, Alexandros Paraschos, Andras Kupcsik, and Jan Peters · 2014
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Deep reinforcement learning in parameterized action space
Matthew Hausknecht and Peter Stone · 2015
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Towards learning hierarchical skills for multi-phase manipulation tasks
Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke Van Hoof, and Jan Peters · 2015
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Learning movement primitive attractor goals and sequential skills from kinesthetic demonstrations
Simon Manschitz, Jens Kober, Michael Gienger, and Jan Peters · 2015
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Logic-geometric programming: An optimization-based approach to combined task and motion planning
Marc Toussaint · 2015
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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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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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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Deep encoder-decoder networks for mapping raw images to dynamic movement primitives
Andrej Gams, Aleš Ude, Jun Morimoto, et al · 2018
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Hierarchical imitation and reinforcement learning
Hoang Le, Nan Jiang, Alekh Agarwal, Miroslav Dudík, Yisong Yue, and Hal Daumé III · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
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One-shot hierarchical imitation learning of compound visuomotor tasks
Tianhe Yu, Pieter Abbeel, Sergey Levine, and Chelsea Finn · 2018
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Hierarchical variational imitation learning of control programs
Roy Fox, Richard Shin, William Paul, Yitian Zou, Dawn Song, Ken Goldberg, Pieter Abbeel, and Ion Stoica · 2019
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Compile: Compositional imitation learning and execution
Thomas Kipf, Yujia Li, Hanjun Dai, Vinicius Zambaldi, Alvaro Sanchez-Gonzalez, Edward Grefenstette, Pushmeet Kohli, and Peter Battaglia · 2019
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Learning to coordinate manipulation skills via skill behavior diversification
Youngwoon Lee, Jingyun Yang, and Joseph J Lim · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne · 2019
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Conditional neural movement primitives
Muhammet Yunus Seker, Mert Imre, Justus H Piater, and Emre Ugur · 2019
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Efficient bimanual manipulation using learned task schemas
Rohan Chitnis, Shubham Tulsiani, Saurabh Gupta, and Abhinav Gupta · 2020
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Towards continual reinforcement learning: A review and perspectives
Augmenting reinforcement learning with behavior primitives for diverse manipulation tasks
Soroush Nasiriany, Huihan Liu, and Yuke Zhu · 2022
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Dual-prompt: Complementary prompting for rehearsal-free continual learning
Zifeng Wang, Zizhao Zhang, Sayna Chen, and Zheng Wang · 2022
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Continual sequence generation with adaptive compositional modules
Yanzhe Zhang, Xuezhi Wang, and Diyi Yang · 2022
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Predicting object interactions with behavior primitives: An application in stowing tasks
Haonan Chen, Yilong Niu, Kaiwen Hong, Shuijing Liu, Yixuan Wang, Yunzhu Li, and Katherine Rose Driggs-Campbell · 2023
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League: Guided skill learning and abstraction for long-horizon manipulation
Shuo Cheng and Danfei Xu · 2023
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Coda-prompt: Continual decomposed attention-based prompting for rehearsal-free continual learning
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Khimya Khetarpal, Matthew Riemer, Irina Rish, and Doina Precup · 2020
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Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, and Natalia Díaz-Rodríguez · 2020
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Toward training recurrent neural networks for lifelong learning
Shagun Sodhani, Sarath Chandar, and Yoshua Bengio · 2020
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Learning to combine primitive skills: A step towards versatile robotic manipulation §
Robin Strudel, Alexander Pashevich, Igor Kalevatykh, Ivan Laptev, Josef Sivic, and Cordelia Schmid · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Brain-inspired replay for continual learning with artificial neural networks
Gido M van de Ven, Hava T Siegelmann, and Andreas S Tolias · 2020
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Deep imitation learning for bimanual robotic manipulation
Fan Xie, Alexander Chowdhury, M De Paolis Kaluza, Linfeng Zhao, Lawson Wong, and Rose Yu · 2020
Cited alongside, same era.
Zifeng Jiang, Hao Zhang, Tianlong Cai, Hang Zhao, Ying Ding, Zheng Wang, Shu Wang, and Yun Wang · 2023
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Mimicgen: A data generation system for scalable robot learning using human demonstrations
Ajay Mandlekar, Soroush Nasiriany, Bowen Wen, Iretiayo Akinola, Yashraj Narang, Linxi Fan, Yuke Zhu, and Dieter Fox · 2023
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Lifelong sequence generation with dynamic module expansion and adaptation
Chengwei Qin, Chen Chen, and Shafiq Joty · 2023
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Waypoint-based imitation learning for robotic manipulation
Lucy Xiaoyang Shi, Archit Sharma, Tony Z Zhao, and Chelsea Finn · 2023
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Orthogonal subspace learning for language model continual learning
Xiao Wang, Tianze Chen, Qiming Ge, Han Xia, Rong Bao, Rui Zheng, Qi Zhang, Tao Gui, and Xuanjing Huang · 2023
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Prime: Scaffolding manipulation tasks with behavior primitives for data-efficient imitation learning
Tian Gao, Soroush Nasiriany, Huihan Liu, Quantao Yang, and Yuke Zhu · 2024
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Chain-of-thought predictive control
Zhiwei Jia, Vineet Thumuluri, Fangchen Liu, Linghao Chen, Zhiao Huang, and Hao Su · 2024
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Infocon: concept discovery with generative and discriminative informativeness
Ruizhe Liu, Qian Luo, and Yanchao Yang · 2024
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Implicit event-rgbd neural slam
Delin Qu, Chi Yan, Dong Wang, Jie Yin, Qizhi Chen, Yiting Zhang, Dan Xu, Bin Zhao, and Xuelong Li · 2024
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Lotus: Continual imitation learning for robot manipulation through unsupervised skill discovery
Weikang Wan, Yifeng Zhu, Rutav Shah, and Yuke Zhu · 2024
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Sparse diffusion policy: A sparse, reusable, and flexible policy for robot learning
Yixiao Wang, Yifei Zhang, Mingxiao Huo, Ran Tian, Xiang Zhang, Yichen Xie, Chenfeng Xu, Pengliang Ji, Wei Zhan, Mingyu Ding, et al · 2024
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Gs-slam: Dense visual slam with 3d gaussian splatting
Chi Yan, Delin Qu, Dan Xu, Bin Zhao, Zhigang Wang, Dong Wang, and Xuelong Li · 2024
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SAPT: A shared attention framework for parameter-efficient continual learning of large language models
Weixiang Zhao, Shilong Wang, Yulin Hu, Yanyan Zhao, Bing Qin, Xuanyu Zhang, Qing Yang, Dongliang Xu, and Wanxiang Che · 2024
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Maxmi: A maximal mutual information criterion for manipulation concept discovery
Pei Zhou and Yanchao Yang · 2024
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Spatialvla: Exploring spatial representations for visual-language-action model
Delin Qu, Haoming Song, Qizhi Chen, Yuanqi Yao, Xinyi Ye, Yan Ding, Zhigang Wang, JiaYuan Gu, Bin Zhao, Dong Wang, et al · 2025
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