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High-quality benchmarks are the foundation for embodied AI research, enabling significant advancements in long-horizon navigation, manipulation and rearrangement tasks.
A framework for behavioural cloning
Michael Bain and Claude Sammut · 1995
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Benchmarking in manipulation research: The YCB object and model set and benchmarking protocols
Berk Çalli, Aaron Walsman, Arjun Singh, Siddhartha S. Srinivasa, Pieter Abbeel, and Aaron M. Dollar · 2015
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End to end learning for self-driving cars
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Learning transferable policies for monocular reactive MAV control
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AI2-THOR: an interactive 3d environment for visual AI
Eric Kolve, Roozbeh Mottaghi, Daniel Gordon, Yuke Zhu, Abhinav Gupta, and Ali Farhadi · 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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Distributed distributional deterministic policy gradients
Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, and Timothy P. Lillicrap · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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ROBOTURK: A crowdsourcing platform for robotic skill learning through imitation
Ajay Mandlekar, Yuke Zhu, Animesh Garg, Jonathan Booher, Max Spero, Albert Tung, Julian Gao, John Emmons, Anchit Gupta, Emre Orbay, Silvio Savarese, and Li Fei-Fei · 2018
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Robonet: Large-scale multi-robot learning
Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, and Chelsea Finn · 2019
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Habitat: A platform for embodied AI research
Manolis Savva, Jitendra Malik, Devi Parikh, Dhruv Batra, Abhishek Kadian, Oleksandr Maksymets, Yili Zhao, Erik Wijmans, Bhavana Jain, Julian Straub, Jia Liu, and Vladlen Koltun · 2019
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D4RL: datasets for deep data-driven reinforcement learning
Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, and Sergey Levine · 2020
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Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J. Davison · 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, Li Yi, Angel X. Chang, Leonidas J. Guibas, and Hao Su · 2020
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robosuite: A modular simulation framework and benchmark for robot learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar, and Roberto Martín-Martín · 2020
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Adversarial skill chaining for long-horizon robot manipulation via terminal state regularization
Youngwoon Lee, Joseph J. Lim, Anima Anandkumar, and Yuke Zhu · 2021
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igibson 2.0: Object-centric simulation for robot learning of everyday household tasks
Chengshu Li, Fei Xia, Roberto Martín-Martín, Michael Lingelbach, Sanjana Srivastava, Bokui Shen, Kent Elliott Vainio, Cem Gokmen, Gokul Dharan, Tanish Jain, Andrey Kurenkov, C. Karen Liu, Hyowon Gweon, Jiajun Wu, Li Fei-Fei, and Silvio Savarese · 2021
Sequential dexterity: Chaining dexterous policies for long-horizon manipulation
Yuanpei Chen, Chen Wang, Li Fei-Fei, and C. Karen Liu · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, and Shuran Song · 2023
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Multi-skill mobile manipulation for object rearrangement
Jiayuan Gu, Devendra Singh Chaplot, Hao Su, and Jitendra Malik · 2023
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Maniskill2: A unified benchmark for generalizable manipulation skills
Jiayuan Gu, Fanbo Xiang, Xuanlin Li, Zhan Ling, Xiqiang Liu, Tongzhou Mu, Yihe Tang, Stone Tao, Xinyue Wei, Yunchao Yao, Xiaodi Yuan, Pengwei Xie, Zhiao Huang, Rui Chen, and Hao Su · 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 S. Narang, Linxi Fan, Yuke Zhu, and Dieter Fox · 2023
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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Habitat 2.0: Training home assistants to rearrange their habitat
Andrew Szot, Alexander Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John M. Turner, Noah Maestre, Mustafa Mukadam, Devendra Singh Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel X. Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, and Dhruv Batra · 2021
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Procthor: Large-scale embodied AI using procedural generation
Matt Deitke, Eli VanderBilt, Alvaro Herrasti, Luca Weihs, Kiana Ehsani, Jordi Salvador, Winson Han, Eric Kolve, Aniruddha Kembhavi, and Roozbeh Mottaghi · 2022
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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 · 2022
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The threedworld transport challenge: A visually guided task-and-motion planning benchmark towards physically realistic embodied AI
Chuang Gan, Siyuan Zhou, Jeremy Schwartz, Seth Alter, Abhishek Bhandwaldar, Dan Gutfreund, Daniel L. K. Yamins, James J. DiCarlo, Josh H. McDermott, Antonio Torralba, and Joshua B. Tenenbaum · 2022
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Cleanrl: High-quality single-file implementations of deep reinforcement learning algorithms
Shengyi Huang, Rousslan Fernand Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, and João G.M. Araújo · 2022
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BEHAVIOR-1K: A benchmark for embodied AI with 1, 000 everyday activities and realistic simulation
Chengshu Li, Ruohan Zhang, Josiah Wong, Cem Gokmen, Sanjana Srivastava, Roberto Martín-Martín, Chen Wang, Gabrael Levine, Michael Lingelbach, Jiankai Sun, Mona Anvari, Minjune Hwang, Manasi Sharma, Arman Aydin, Dhruva Bansal, Samuel Hunter, Kyu-Young Kim, Alan Lou, Caleb R. Matthews, Ivan Villa-Renteria, Jerry Huayang Tang, Claire Tang, Fei Xia, Silvio Savarese, Hyowon Gweon, C. Karen Liu, Jiajun Wu, and Li Fei-Fei · 2022
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Later among the works it cites.
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 · 2024
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Open x-embodiment: Robotic learning datasets and RT-X models : Open x-embodiment collaboration
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DROID: A large-scale in-the-wild robot manipulation dataset
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Robocasa: Large-scale simulation of everyday tasks for generalist robots
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Diffusion policy policy optimization
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Maniskill3: Gpu parallelized robotics simulation and rendering for generalizable embodied ai
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Learning interactive real-world simulators
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Autonomous mobile robots, 2024
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