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Building general-purpose robots that operate seamlessly in any environment, with any object, and utilizing various skills to complete diverse tasks has been a long-standing goal in Artificial Intelligence.
Design and use paradigms for gazebo, an open-source multi-robot simulator
N. Koenig and A. Howard · 2004
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Using a hand-drawn sketch to control a team of robots
Marjorie Skubic, Derek Anderson, Samuel Blisard, Dennis Perzanowski, and Alan Schultz · 2007
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Integration of action and language knowledge: A roadmap for developmental robotics
Angelo Cangelosi, Giorgio Metta, Gerhard Sagerer, Stefano Nolfi, Chrystopher Nehaniv, Kerstin Fischer, Jun Tani, Tony Belpaeme, Giulio Sandini, Francesco Nori, and et al · 2010
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Modular and hierarchically modular organization of brain networks
David Meunier, Renaud Lambiotte, and Edward T Bullmore · 2010
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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The arcade learning environment: An evaluation platform for general agents
Marc G Bellemare, Yavar Naddaf, Joel Veness, and Michael Bowling · 2013
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Decaf: A deep convolutional activation feature for generic visual recognition
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell · 2014
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Grounding semantic categories in behavioral interactions: Experiments with 100 objects
Jivko Sinapov, Connor Schenck, Kerrick Staley, Vladimir Sukhoy, and Alexander Stoytchev · 2014
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Learning relational object categories using behavioral exploration and multimodal perception
Jivko Sinapov, Connor Schenck, and Alexander Stoytchev · 2014
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Learning haptic representation for manipulating deformable food objects
Mevlana C. Gemici and Ashutosh Saxena · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Aggressive driving with model predictive path integral control
Grady Williams, Paul Drews, Brian Goldfain, James M. Rehg, and Evangelos A. Theodorou · 2016
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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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Sergey Levine, Peter Pastor, Alex Krizhevsky, and Deirdre Quillen · 2016
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Modular brain networks
Olaf Sporns and Richard F Betzel · 2016
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Robotics in mining
Joshua A Marshall, Adrian Bonchis, Eduardo Nebot, and Steven Scheding · 2016
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Yale-cmu-berkeley dataset for robotic manipulation research
Berk Calli, Arjun Singh, James Bruce, Aaron Walsman, Kurt Konolige, Siddhartha Srinivasa, Pieter Abbeel, and Aaron M Dollar · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Hamilton-jacobi reachability: A brief overview and recent advances
Somil Bansal, Mo Chen, Sylvia Herbert, and Claire J Tomlin · 2017
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Interactive perception: Leveraging action in perception and perception in action
Jeannette Bohg, Karol Hausman, Bharath Sankaran, Oliver Brock, Danica Kragic, Stefan Schaal, and Gaurav S. Sukhatme · 2017
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One-shot imitation learning
Yan Duan, Marcin Andrychowicz, Bradly Stadie, OpenAI Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, and Wojciech Zaremba · 2017
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One-shot visual imitation learning via meta-learning
Chelsea Finn, Tianhe Yu, Tianhao Zhang, Pieter Abbeel, and Sergey Levine · 2017
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Modular multitask reinforcement learning with policy sketches
Jacob Andreas, Dan Klein, and Sergey Levine · 2017
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Matterport3d: Learning from rgb-d data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
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Ai2-thor: An interactive 3d environment for visual ai
Eric Kolve, Roozbeh Mottaghi, Winson Han, Eli VanderBilt, Luca Weihs, Alvaro Herrasti, Matt Deitke, Kiana Ehsani, Daniel Gordon, Yuke Zhu, et al · 2017
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Airsim: High-fidelity visual and physical simulation for autonomous vehicles, 2017
Shital Shah, Debadeepta Dey, Chris Lovett, and Ashish Kapoor · 2017
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Improved gelsight tactile sensor for measuring geometry and slip
Siyuan Dong, Wenzhen Yuan, and Edward H. Adelson · 2017
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Active incremental learning of robot movement primitives
Guilherme Maeda, Marco Ewerton, Takayuki Osa, Baptiste Busch, and Jan Peters · 2017
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Meta learning shared hierarchies, 2017
Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, and John Schulman · 2017
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Working together: A review on safe human-robot collaboration in industrial environments
Sandra Robla-Gómez, Victor M Becerra, José Ramón Llata, Esther Gonzalez-Sarabia, Carlos Torre-Ferrero, and Juan Perez-Oria · 2017
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Imagination-augmented agents for deep reinforcement learning
Théophane Weber, Sébastien Racaniere, David P Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adria Puigdomenech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, et al · 2017
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Real-time semantic mapping for autonomous off-road navigation
Daniel Maturana, Po-Wei Chou, Masashi Uenoyama, and Sebastian Scherer · 2018
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Qt-opt: Scalable deep reinforcement learning for vision-based robotic manipulation
Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, and Sergey Levine · 2018
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Vision-and-language navigation: Interpreting visually-grounded navigation instructions in real environments
Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian Reid, Stephen Gould, and Anton Van Den Hengel · 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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One-shot imitation from observing humans via domain-adaptive meta-learning
Tianhe Yu, Chelsea Finn, Annie Xie, Sudeep Dasari, Tianhao Zhang, Pieter Abbeel, and Sergey Levine · 2018
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Vision-based multi-task manipulation for inexpensive robots using end-to-end learning from demonstration
Rouhollah Rahmatizadeh, Pooya Abolghasemi, Ladislau Bölöni, and Sergey Levine · 2018
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Gibson env: Real-world perception for embodied agents
Fei Xia, Amir R Zamir, Zhiyang He, Alexander Sax, Jitendra Malik, and Silvio Savarese · 2018
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A new concept of safety affordance map for robots object manipulation
S.H. Cheong, J.H. Lee, and C.H. Kim · 2018
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The end-to-end false dichotomy: Roboticists arguing lego vs. playmo
Vincent Vanhoucke · 2018
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Quantized neural networks: Training neural networks with low precision weights and activations
Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Bengio · 2018
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Babyai: A platform to study the sample efficiency of grounded language learning
Maxime Chevalier-Boisvert, Dzmitry Bahdanau, Salem Lahlou, Lucas Willems, Chitwan Saharia, Thien Huu Nguyen, and Yoshua Bengio · 2018
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Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al · 2018
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Minimalistic gridworld environment for gymnasium
M. Chevalier-Boisvert, L. Willems, and S. Pal · 2018
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Learning agile and dynamic motor skills for legged robots
Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, and Marco Hutter · 2019
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Deep dynamics models for learning dexterous manipulation
Anusha Nagabandi, Kurt Konoglie, Sergey Levine, and Vikash Kumar · 2019
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Habitat: A platform for embodied ai research
Manolis Savva, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, et al · 2019
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Control barrier functions: Theory and applications
Aaron D Ames, Samuel Coogan, Magnus Egerstedt, Gennaro Notomista, Koushil Sreenath, and Paulo Tabuada · 2019
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Sensorimotor cross-behavior knowledge transfer for grounded category recognition
Gyan Tatiya, Ramtin Hosseini, Michael C. Hughes, and Jivko Sinapov · 2019
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Watch, try, learn: Meta-learning from demonstrations and reward
Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, and Chelsea Finn · 2019
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Habitat: A Platform for Embodied AI Research
Manolis Savva*, Abhishek Kadian*, Oleksandr Maksymets*, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, Vladlen Koltun, Jitendra Malik, Devi Parikh, and Dhruv Batra · 2019
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Solving rubik’s cube with a robot hand, 2019
OpenAI, Ilge Akkaya, Marcin Andrychowicz, Maciek Chociej, Mateusz Litwin, Bob McGrew, Arthur Petron, Alex Paino, Matthias Plappert, Glenn Powell, Raphael Ribas, Jonas Schneider, Nikolas Tezak, Jerry Tworek, Peter Welinder, Lilian Weng, Qiming Yuan, Wojciech Zaremba, and Lei Zhang · 2019
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Slowfast networks for video recognition, 2019
Christoph Feichtenhofer, Haoqi Fan, Jitendra Malik, and Kaiming He · 2019
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Learning to teach in cooperative multiagent reinforcement learning
Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, and Jonathan P. How · 2019
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Learning domain-independent planning heuristics with hypergraph networks
William Shen, Felipe Trevizan, and Sylvie Thiébaux · 2020
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Learning value functions with relational state representations for guiding task-and-motion planning
Beomjoon Kim and Luke Shimanuki · 2020
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Motion planning networks: Bridging the gap between learning-based and classical motion planners
Ahmed H Qureshi, Yinglong Miao, Anthony Simeonov, and Michael C Yip · 2020
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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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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2020
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Provably constant-time planning and replanning for real-time grasping objects off a conveyor belt
Fahad Islam, Oren Salzman, Aditya Agarwal, and Maxim Likhachev · 2020
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Integrated Task and Motion Planning
Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, and Tomas Lozano-P´erez · 2020
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Just ask: An interactive learning framework for vision and language navigation
Ta-Chung Chi, Minmin Shen, Mihail Eric, Seokhwan Kim, and Dilek Hakkani-tur · 2020
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A framework for sensorimotor cross-perception and cross-behavior knowledge transfer for object categorization
Gyan Tatiya, Ramtin Hosseini, Michael Hughes, and Jivko Sinapov · 2020
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Haptic knowledge transfer between heterogeneous robots using kernel manifold alignment
Gyan Tatiya, Yash Shukla, Michael Edegware, and Jivko Sinapov · 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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Learning one-shot imitation from humans without humans
Alessandro Bonardi, Stephen James, and Andrew J Davison · 2020
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Language conditioned imitation learning over unstructured data
Corey Lynch and Pierre Sermanet · 2020
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Language-conditioned imitation learning for robot manipulation tasks
Simon Stepputtis, Joseph Campbell, Mariano Phielipp, Stefan Lee, Chitta Baral, and Heni Ben Amor · 2020
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Conservative q-learning for offline reinforcement learning
Aviral Kumar, Aurick Zhou, George Tucker, and Sergey Levine · 2020
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Robonet: Large-scale multi-robot learning, 2020
Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, and Chelsea Finn · 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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Hierarchical foresight: Self-supervised learning of long-horizon tasks via visual subgoal generation
Suraj Nair and Chelsea Finn · 2020
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Sensor-based and vision-based human activity recognition: A comprehensive survey
L Minh Dang, Kyungbok Min, Hanxiang Wang, Md Jalil Piran, Cheol Hee Lee, and Hyeonjoon Moon · 2020
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Sapien: A simulated part-based interactive environment
Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, et al · 2020
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Transporter networks: Rearranging the visual world for robotic manipulation
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, and Johnny Lee · 2020
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Leveraging procedural generation to benchmark reinforcement learning
Karl Cobbe, Chris Hesse, Jacob Hilton, and John Schulman · 2020
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Mt-opt: Continuous multi-task robotic reinforcement learning at scale
Dmitry Kalashnkov, Jake Varley, Yevgen Chebotar, Ben Swanson, Rico Jonschkowski, Chelsea Finn, Sergey Levine, and Karol Hausman · 2021
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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 · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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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, Gretchen Krueger, and Ilya Sutskever · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Learn-to-race: A multimodal control environment for autonomous racing
James Herman, Jonathan Francis, Siddha Ganju, Bingqing Chen, Anirudh Koul, Abhinav Gupta, Alexey Skabelkin, Ivan Zhukov, Max Kumskoy, and Eric Nyberg · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning, 2021
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, and Gavriel State · 2021
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Manipulation planning among movable obstacles using physics-based adaptive motion primitives
Dhruv Mauria Saxena, Muhammad Suhail Saleem, and Maxim Likhachev · 2021
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A gentle introduction to conformal prediction and distribution-free uncertainty quantification
Anastasios N Angelopoulos and Stephen Bates · 2021
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Safe autonomous racing via approximate reachability on ego-vision
Bingqing Chen, Jonathan Francis, Jean Oh, Eric Nyberg, and Sylvia L Herbert · 2021
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Cliport: What and where pathways for robotic manipulation
Mohit Shridhar, Lucas Manuelli, and Dieter Fox · 2021
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Transformers for one-shot visual imitation
Sudeep Dasari and Abhinav Gupta · 2021
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Generalization in dexterous manipulation via geometry-aware multi-task learning
Wenlong Huang, Igor Mordatch, Pieter Abbeel, and Deepak Pathak · 2021
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Bridge data: Boosting generalization of robotic skills with cross-domain datasets, 2021
Frederik Ebert, Yanlai Yang, Karl Schmeckpeper, Bernadette Bucher, Georgios Georgakis, Kostas Daniilidis, Chelsea Finn, and Sergey Levine · 2021
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The mit humanoid robot: Design, motion planning, and control for acrobatic behaviors
Matthew Chignoli, Donghyun Kim, Elijah Stanger-Jones, and Sangbae Kim · 2021
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Model-free safe control for zero-violation reinforcement learning
Weiye Zhao, Tairan He, and Changliu Liu · 2021
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Scalable learning of safety guarantees for autonomous systems using hamilton-jacobi reachability, 2021
Sylvia Herbert, Jason J. Choi, Suvansh Sanjeev, Marsalis Gibson, Koushil Sreenath, and Claire J. Tomlin · 2021
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Rma: Rapid motor adaptation for legged robots
Ashish Kumar, Zipeng Fu, Deepak Pathak, and Jitendra Malik · 2021
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Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks
Lin Wang and Kuk-Jin Yoon · 2021
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The surprising effectiveness of representation learning for visual imitation
Jyothish Pari, Nur Muhammad Shafiullah, Sridhar Pandian Arunachalam, and Lerrel Pinto · 2021
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Where2act: From pixels to actions for articulated 3d objects, 2021
Kaichun Mo, Leonidas Guibas, Mustafa Mukadam, Abhinav Gupta, and Shubham Tulsiani · 2021
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Beyond pick-and-place: Tackling robotic stacking of diverse shapes, 2021
Alex X. Lee, Coline Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin Riedmiller, Raia Hadsell, and Francesco Nori · 2021
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning, 2021
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Avnish Narayan, Hayden Shively, Adithya Bellathur, Karol Hausman, Chelsea Finn, and Sergey Levine · 2021
Cited alongside, same era.
Motion policy networks
Yilun Du, Mengjiao Yang, Pete Florence, Fei Xia, Ayzaan Wahid, Brian Ichter, Pierre Sermanet, Tianhe Yu, Pieter Abbeel, Joshua B Tenenbaum, et al · 2023
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Text2motion: From natural language instructions to feasible plans
Kevin Lin, Christopher Agia, Toki Migimatsu, Marco Pavone, and Jeannette Bohg · 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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Gensim: Generating robotic simulation tasks via large language models
Lirui Wang, Yiyang Ling, Zhecheng Yuan, Mohit Shridhar, Chen Bao, Yuzhe Qin, Bailin Wang, Huazhe Xu, and Xiaolong Wang · 2023
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Sayplan: Grounding large language models using 3d scene graphs for scalable task planning
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Adam Fishman, Adithyavairavan Murali, Clemens Eppner, Bryan Peele, Byron Boots, and Dieter Fox · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal Alex Nichol, Casey Chu, and Mark Chen · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar, Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi · 2022
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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, Katie Millican, Malcolm Reynolds, Roman Ring, Eliza Rutherford, Serkan Cabi, Tengda Han, Zhitao Gong, Sina Samangooei, Marianne Monteiro, Jacob Menick, Sebastian Borgeaud, Andy Brock, Aida Nematzadeh, Sahand Sharifzadeh, Mikolaj Binkowski, Ricardo Barreira, Oriol Vinyals, Andrew Zisserman, and Karen Simonyan · 2022
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Do as i can, 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, et al · 2022
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Open-vocabulary queryable scene representations for real world planning
Boyuan Chen, Fei Xia, Brian Ichter, Kanishka Rao, Keerthana Gopalakrishnan, Michael S. Ryoo, Austin Stone, and Daniel Kappler · 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
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A generalist agent
Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, and Nando de Freitas · 2022
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Krishan Rana, Jesse Haviland, Sourav Garg, Jad Abou-Chakra, Ian Reid, and Niko Suenderhauf · 2023
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Reasoning about the unseen for efficient outdoor object navigation, 2023
Quanting Xie, Tianyi Zhang, Kedi Xu, Matthew Johnson-Roberson, and Yonatan Bisk · 2023
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How to not train your dragon: Training-free embodied object goal navigation with semantic frontiers
Junting Chen, Guohao Li, Suryansh Kumar, Bernard Ghanem, and Fisher Yu · 2023
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Voxposer: Composable 3d value maps for robotic manipulation with language models
Wenlong Huang, Chen Wang, Ruohan Zhang, Yunzhu Li, Jiajun Wu, and Li Fei-Fei · 2023
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Prompt a robot to walk with large language models, 2023
Yen-Jen Wang, Bike Zhang, Jianyu Chen, and Koushil Sreenath · 2023
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Guiding pretraining in reinforcement learning with large language models, 2023
Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, and Jacob Andreas · 2023
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Reward design with language models, 2023
Minae Kwon, Sang Michael Xie, Kalesha Bullard, and Dorsa Sadigh · 2023
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Text2reward: Automated dense reward function generation for reinforcement learning, 2023
Tianbao Xie, Siheng Zhao, Chen Henry Wu, Yitao Liu, Qian Luo, Victor Zhong, Yanchao Yang, and Tao Yu · 2023
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Language to rewards for robotic skill synthesis
Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montse Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, and Fei Xia · 2023
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Pengi: An audio language model for audio tasks, 2023
Soham Deshmukh, Benjamin Elizalde, Rita Singh, and Huaming Wang · 2023
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Anygrasp: Robust and efficient grasp perception in spatial and temporal domains
Hao-Shu Fang, Chenxi Wang, Hongjie Fang, Minghao Gou, Jirong Liu, Hengxu Yan, Wenhai Liu, Yichen Xie, and Cewu Lu · 2023
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Grounding large language models in interactive environments with online reinforcement learning, 2023
Thomas Carta, Clément Romac, Thomas Wolf, Sylvain Lamprier, Olivier Sigaud, and Pierre-Yves Oudeyer · 2023
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Pali-x: On scaling up a multilingual vision and language model, 2023
Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, AJ Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, and Radu Soricut · 2023
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Scaling up and distilling down: Language-guided robot skill acquisition
Huy Ha, Pete Florence, and Shuran Song · 2023
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Robogen: Towards unleashing infinite data for automated robot learning via generative simulation, 2023
Yufei Wang, Zhou Xian, Feng Chen, Tsun-Hsuan Wang, Yian Wang, Katerina Fragkiadaki, Zackory Erickson, David Held, and Chuang Gan · 2023
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Scaling robot learning with semantically imagined experience
Tianhe Yu, Ted Xiao, Austin Stone, Jonathan Tompson, Anthony Brohan, Su Wang, Jaspiar Singh, Clayton Tan, Jodilyn Peralta Dee M, Brian Ichter, Karol Hausman, and Fei Xia · 2023
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Rt-trajectory: Robotic task generalization via hindsight trajectory sketches, 2023
Jiayuan Gu, Sean Kirmani, Paul Wohlhart, Yao Lu, Montserrat Gonzalez Arenas, Kanishka Rao, Wenhao Yu, Chuyuan Fu, Keerthana Gopalakrishnan, Zhuo Xu, Priya Sundaresan, Peng Xu, Hao Su, Karol Hausman, Chelsea Finn, Quan Vuong, and Ted Xiao · 2023
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Zero-shot robotic manipulation with pretrained image-editing diffusion models, 2023
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, and Sergey Levine · 2023
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Learning universal policies via text-guided video generation
Yilun Du, Mengjiao Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, and Pieter Abbeel · 2023
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Chain-of-thought prompting elicits reasoning in large language models, 2023
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, and Denny Zhou · 2023
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Faith and fate: Limits of transformers on compositionality, 2023
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, and Yejin Choi · 2023
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Graph of thoughts: Solving elaborate problems with large language models, 2023
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Michal Podstawski, Hubert Niewiadomski, Piotr Nyczyk, and Torsten Hoefler · 2023
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Tree of thoughts: Deliberate problem solving with large language models, 2023
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, and Karthik Narasimhan · 2023
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Planning with large language models for code generation
Shun Zhang, Zhenfang Chen, Yikang Shen, Mingyu Ding, Joshua B. Tenenbaum, and Chuang Gan · 2023
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Llm+p: Empowering large language models with optimal planning proficiency, 2023
Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone · 2023
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Open-world object manipulation using pre-trained vision-language models
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Mimicplay: Long-horizon imitation learning by watching human play
Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, and Anima Anandkumar · 2023
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Q-transformer: Scalable offline reinforcement learning via autoregressive q-functions
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Pre-training for robots: Offline rl enables learning new tasks from a handful of trials
Aviral Kumar, Anikait Singh, Frederik Ebert, Mitsuhiko Nakamoto, Yanlai Yang, Chelsea Finn, and Sergey Levine · 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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Real-world robot learning with masked visual pre-training
Ilija Radosavovic, Tete Xiao, Stephen James, Pieter Abbeel, Jitendra Malik, and Trevor Darrell · 2023
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Robot learning with sensorimotor pre-training, 2023
Ilija Radosavovic, Baifeng Shi, Letian Fu, Ken Goldberg, Trevor Darrell, and Jitendra Malik · 2023
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On pre-training for visuo-motor control: Revisiting a learning-from-scratch baseline
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Where are we in the search for an artificial visual cortex for embodied intelligence?, 2023
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Affordances from human videos as a versatile representation for robotics
Shikhar Bahl, Russell Mendonca, Lili Chen, Unnat Jain, and Deepak Pathak · 2023
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Dexterity from touch: Self-supervised pre-training of tactile representations with robotic play, 2023
Irmak Guzey, Ben Evans, Soumith Chintala, and Lerrel Pinto · 2023
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Gnm: A general navigation model to drive any robot
Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, and Sergey Levine · 2023
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Indoorsim-to-outdoorreal: Learning to navigate outdoors without any outdoor experience
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Conceptgraphs: Open-vocabulary 3d scene graphs for perception and planning
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Learning interactive real-world simulators
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Towards open vocabulary learning: A survey
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Holistic analysis of hallucination in gpt-4v (ision): Bias and interference challenges
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Physically grounded vision-language models for robotic manipulation
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Bridgedata v2: A dataset for robot learning at scale
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Leap hand: Low-cost, efficient, and anthropomorphic hand for robot learning
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Mujoco 3.0
Google DeepMind · 2023
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Plug in the safety chip: Enforcing constraints for LLM-driven robot agents
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Dexterous hand series
Shadow Robot Company · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware, 2023
Tony Z. Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
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An empirical investigation of the role of pre-training in lifelong learning
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Construct-vl: Data-free continual structured vl concepts learning
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Inverse preference learning: Preference-based rl without a reward function, 2023
Joey Hejna and Dorsa Sadigh · 2023
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Reinforcement learning with human feedback: Learning dynamic choices via pessimism, 2023
Zihao Li, Zhuoran Yang, and Mengdi Wang · 2023
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Sample efficient reinforcement learning from human feedback via active exploration, 2023
Viraj Mehta, Vikramjeet Das, Ojash Neopane, Yijia Dai, Ilija Bogunovic, Jeff Schneider, and Willie Neiswanger · 2023
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Direct preference-based policy optimization without reward modeling, 2023
Gaon An, Junhyeok Lee, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, and Hyun Oh Song · 2023
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Compositional foundation models for hierarchical planning, 2023
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Imitating task and motion planning with visuomotor transformers
Murtaza Dalal, Ajay Mandlekar, Caelan Garrett, Ankur Handa, Ruslan Salakhutdinov, and Dieter Fox · 2023
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Extreme parkour with legged robots
Xuxin Cheng, Kexin Shi, Ananye Agarwal, and Deepak Pathak · 2023
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Reflect: Summarizing robot experiences for failure explanation and correction
Zeyi Liu, Arpit Bahety, and Shuran Song · 2023
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A case for business process-specific foundation models
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Conceptfusion: Open-set multimodal 3d mapping
Krishna Murthy Jatavallabhula, Alihusein Kuwajerwala, Qiao Gu, et al · 2023
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Playfusion: Skill acquisition via diffusion from language-annotated play
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Clvr jaco play dataset
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Multi-stage cable routing through hierarchical imitation learning, 2023
Jianlan Luo, Charles Xu, Xinyang Geng, Gilbert Feng, Kuan Fang, Liam Tan, Stefan Schaal, and Sergey Levine · 2023
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Chat with the environment: Interactive multimodal perception using large language models, 2023
Xufeng Zhao, Mengdi Li, Cornelius Weber, Muhammad Burhan Hafez, and Stefan Wermter · 2023
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Instruct2act: Mapping multi-modality instructions to robotic actions with large language model, 2023
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Large language models as generalizable policies for embodied tasks, 2023
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Liv: Language-image representations and rewards for robotic control, 2023
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Tidybot: Personalized robot assistance with large language models
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Task and motion planning with large language models for object rearrangement
Yan Ding, Xiaohan Zhang, Chris Paxton, and Shiqi Zhang · 2023
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Habitat-matterport 3d semantics dataset, 2023
Karmesh Yadav, Ram Ramrakhya, Santhosh Kumar Ramakrishnan, Theo Gervet, John Turner, Aaron Gokaslan, Noah Maestre, Angel Xuan Chang, Dhruv Batra, Manolis Savva, Alexander William Clegg, and Devendra Singh Chaplot · 2023
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Grounded decoding: Guiding text generation with grounded models for robot control
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Openvla: An open-source vision-language-action model, 2024
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Sriram Yenamandra, Arun Ramachandran, Mukul Khanna, Karmesh Yadav, Jay Vakil, Andrew Melnik, Michael Büttner, Leon Harz, Lyon Brown, Gora Chand Nandi, et al · 2024
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RH20T: A comprehensive robotic dataset for learning diverse skills in one-shot
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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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Learning generalizable feature fields for mobile manipulation, 2024
Ri-Zhao Qiu*, Yafei Hu*, Ge Yang, Yuchen Song, Yang Fu, Jianglong Ye, Jiteng Mu, Ruihan Yang, Nikolay Atanasov, Sebastian Scherer, and Xiaolong Wang · 2024
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Mosaic: Learning unified multi-sensory object property representations for robot learning via interactive perception
Gyan Tatiya, Jonathan Francis, Ho-Hsiang Wu, Yonatan Bisk, and Jivko Sinapov · 2024
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Embodied Uncertainty-Aware Object Segmentation
Xiaolin Fang, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2024
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Rekep: Spatio-temporal reasoning of relational keypoint constraints for robotic manipulation
Wenlong Huang, Chen Wang, Yunzhu Li, Ruohan Zhang, and Li Fei-Fei · 2024
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Autort: Embodied foundation models for large scale orchestration of robotic agents, 2024
Michael Ahn, Debidatta Dwibedi, Chelsea Finn, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Karol Hausman, Brian Ichter, Alex Irpan, Nikhil Joshi, Ryan Julian, Sean Kirmani, Isabel Leal, Edward Lee, Sergey Levine, Yao Lu, Isabel Leal, Sharath Maddineni, Kanishka Rao, Dorsa Sadigh, Pannag Sanketi, Pierre Sermanet, Quan Vuong, Stefan Welker, Fei Xia, Ted Xiao, Peng Xu, Steve Xu, and Zhuo Xu · 2024
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Flexcap: Generating rich, localized, and flexible captions in images, 2024
Debidatta Dwibedi, Vidhi Jain, Jonathan Tompson, Andrew Zisserman, and Yusuf Aytar · 2024
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Vid2robot: End-to-end video-conditioned policy learning with cross-attention transformers, 2024
Vidhi Jain, Maria Attarian, Nikhil J Joshi, Ayzaan Wahid, Danny Driess, Quan Vuong, Pannag R Sanketi, Pierre Sermanet, Stefan Welker, Christine Chan, Igor Gilitschenski, Yonatan Bisk, and Debidatta Dwibedi · 2024
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Scaling cross-embodied learning: One policy for manipulation, navigation, locomotion and aviation
Ria Doshi, Homer Walke, Oier Mees, Sudeep Dasari, and Sergey Levine · 2024
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Video generation models as world simulators
Tim Brooks, Bill Peebles, Connor Holmes, Will DePue, Yufei Guo, Li Jing, David Schnurr, Joe Taylor, Troy Luhman, Eric Luhman, Clarence Ng, Ricky Wang, and Aditya Ramesh · 2024
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Genie: Generative interactive environments, 2024
Jake Bruce, Michael Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal Behbahani, Stephanie Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, and Tim Rocktäschel · 2024
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Branden Romero, Hao-Shu Fang, Pulkit Agrawal, and Edward Adelson · 2024
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Airexo: Low-cost exoskeletons for learning whole-arm manipulation in the wild
Hongjie Fang, Hao-Shu Fang, Yiming Wang, Jieji Ren, Jingjing Chen, Ruo Zhang, Weiming Wang, and Cewu Lu · 2024
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Foundationpose: Unified 6d pose estimation and tracking of novel objects, 2024
Bowen Wen, Wei Yang, Jan Kautz, and Stan Birchfield · 2024
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Large language models for automated data science: Introducing caafe for context-aware automated feature engineering
Noah Hollmann, Samuel Müller, and Frank Hutter · 2024
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Open-fusion: Real-time open-vocabulary 3d mapping and queryable scene representation
Kashu Yamazaki, Taisei Hanyu, Khoa Vo, Thang Pham, Minh Tran, Gianfranco Doretto, Anh Nguyen, and Ngan Le · 2024
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Humanoid locomotion as next token prediction
Ilija Radosavovic, Bike Zhang, Baifeng Shi, Jathushan Rajasegaran, Sarthak Kamat, Trevor Darrell, Koushil Sreenath, and Jitendra Malik · 2024
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