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Legged robots are physically capable of navigating a diverse variety of environments and overcoming a wide range of obstructions.
Model predictive control: Theory and practice—a survey
C. E. Garcia, D. M. Prett, and M. Morari · 1989
Earlier work this paper cites.
Model predictive control: past, present and future
M. Morari and J. H. Lee · 1999
Earlier work this paper cites.
Walk the talk: Connecting language, knowledge, and action in route instructions
M. MacMahon, B. Stankiewicz, and B. Kuipers · 2006
Earlier work this paper cites.
Toward understanding natural language directions
T. Kollar, S. Tellex, D. Roy, and N. Roy · 2010
Earlier work this paper cites.
Whole-body motion planning with centroidal dynamics and full kinematics
H. Dai, A. Valenzuela, and R. Tedrake · 2014
Earlier work this paper cites.
Reinforcement learning with multi-fidelity simulators
M. Cutler, T. J. Walsh, and J. P. How · 2014
Earlier work this paper cites.
Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
S. Kuindersma, R. Deits, M. Fallon, A. Valenzuela, H. Dai, F. Permenter, T. Koolen, P. Marion, and R. Tedrake · 2016
Earlier work this paper cites.
Anymal - a highly mobile and dynamic quadrupedal robot
M. Hutter, C. Gehring, D. Jud, A. Lauber, D. Bellicoso, V. Tsounis, J. Hwangbo, K. Bodie, P. Fankhauser, M. Bloesch, R. Diethelm, S. Bachmann, A. Melzer, and M. Höpflinger · 2016
Earlier work this paper cites.
Epopt: Learning robust neural network policies using model ensembles
A. Rajeswaran, S. Ghotra, B. Ravindran, and S. Levine · 2016
Earlier work this paper cites.
Cad2rl: Real single-image flight without a single real image
F. Sadeghi and S. Levine · 2016
Earlier work this paper cites.
Tell me dave: Context-sensitive grounding of natural language to manipulation instructions
D. K. Misra, J. Sung, K. Lee, and A. Saxena · 2016
Earlier work this paper cites.
Deep visual foresight for planning robot motion
C. Finn and S. Levine · 2017
Earlier work this paper cites.
High-speed bounding with the mit cheetah 2: Control design and experiments
H.-W. Park, P. M. Wensing, and S. Kim · 2017
Earlier work this paper cites.
Domain randomization for transferring deep neural networks from simulation to the real world
J. Tobin, R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel · 2017
Earlier work this paper cites.
The option-critic architecture
P.-L. Bacon, J. Harb, and D. Precup · 2017
Earlier work this paper cites.
Visual foresight: Model-based deep reinforcement learning for vision-based robotic control
F. Ebert, C. Finn, S. Dasari, A. Xie, A. Lee, and S. Levine · 2018
Earlier work this paper cites.
Dynamic locomotion through online nonlinear motion optimization for quadrupedal robots
D. Bellicoso, F. Jenelten, C. Gehring, and M. Hutter · 2018
Earlier work this paper cites.
Mit cheetah 3: Design and control of a robust, dynamic quadruped robot
G. Bledt, M. J. Powell, B. Katz, J. Carlo, P. Wensing, and S. Kim · 2018
Earlier work this paper cites.
Learning to walk via deep reinforcement learning
T. Haarnoja, S. Ha, A. Zhou, J. Tan, G. Tucker, and S. Levine · 2018
Earlier work this paper cites.
Sim-to-real: Learning agile locomotion for quadruped robots
J. Tan, T. Zhang, E. Coumans, A. Iscen, Y. Bai, D. Hafner, S. Bohez, and V. Vanhoucke · 2018
Earlier work this paper cites.
Sim-to-real transfer of robotic control with dynamics randomization
X. B. Peng, M. Andrychowicz, W. Zaremba, and P. Abbeel · 2018
Earlier work this paper cites.
Data-efficient hierarchical reinforcement learning
O. Nachum, S. S. Gu, H. Lee, and S. Levine · 2018
Earlier work this paper cites.
Learning agile and dynamic motor skills for legged robots
J. Hwangbo, J. Lee, A. Dosovitskiy, D. Bellicoso, V. Tsounis, V. Koltun, and M. Hutter · 2019
Earlier work this paper cites.
Mini cheetah: A platform for pushing the limits of dynamic quadruped control
B. Katz, J. Carlo, and S. Kim · 2019
Earlier work this paper cites.
Data efficient reinforcement learning for legged robots
Y. Yang, K. Caluwaerts, A. Iscen, T. Zhang, J. Tan, and V. Sindhwani · 2019
Earlier work this paper cites.
Sim-to-real transfer for biped locomotion
W. Yu, V. C. Kumar, G. Turk, and C. K. Liu · 2019
Earlier work this paper cites.
Solving rubik’s cube with a robot hand
I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B. McGrew, A. Petron, A. Paino, M. Plappert, G. Powell, R. Ribas, et al · 2019
Earlier work this paper cites.
Mcp: Learning composable hierarchical control with multiplicative compositional policies
X. B. Peng, M. Chang, G. Zhang, P. Abbeel, and S. Levine · 2019
Cited alongside, same era.
Learning to coordinate manipulation skills via skill behavior diversification
Y. Lee, J. Yang, and J. J. Lim · 2019
Cited alongside, same era.
Learning quadrupedal locomotion over challenging terrain
J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter · 2020
Cited alongside, same era.
Learning agile robotic locomotion skills by imitating animals
X. B. Peng, E. Coumans, T. Zhang, T.-W. Lee, J. Tan, and S. Levine · 2020
Cited alongside, same era.
Learning fast adaptation with meta strategy optimization
W. Yu, J. Tan, Y. Bai, E. Coumans, and S. Ha · 2020
Cited alongside, same era.
Learning to compose hierarchical object-centric controllers for robotic manipulation
You only live once: Single-life reinforcement learning
A. Chen, A. Sharma, S. Levine, and C. Finn · 2022
Later among the works it cites.
Socratic models: Composing zero-shot multimodal reasoning with language
A. Zeng, M. Attarian, B. Ichter, K. Choromanski, A. Wong, S. Welker, F. Tombari, A. Purohit, M. Ryoo, V. Sindhwani, et al · 2022
Later among the works it cites.
Rethinking the role of demonstrations: What makes in-context learning work?
S. Min, X. Lyu, A. Holtzman, M. Artetxe, M. Lewis, H. Hajishirzi, and L. Zettlemoyer · 2022
Later among the works it cites.
A survey on in-context learning
Q. Dong, L. Li, D. Dai, C. Zheng, Z. Wu, B. Chang, X. Sun, J. Xu, and Z. Sui · 2022
Later among the works it cites.
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M. Sharma, J. Liang, J. Zhao, A. LaGrassa, and O. Kroemer · 2020
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Learning to combine primitive skills: A step towards versatile robotic manipulation
R. Strudel, A. Pashevich, I. Kalevatykh, I. Laptev, J. Sivic, and C. Schmid · 2020
Cited alongside, same era.
Efficient bimanual manipulation using learned task schemas
R. Chitnis, S. Tulsiani, S. Gupta, and A. Gupta · 2020
Cited alongside, same era.
Language-conditioned imitation learning for robot manipulation tasks
S. Stepputtis, J. Campbell, M. Phielipp, S. Lee, C. Baral, and H. Ben Amor · 2020
Cited alongside, same era.
Learning vision-guided quadrupedal locomotion end-to-end with cross-modal transformers
R. Yang, M. Zhang, N. Hansen, H. Xu, and X. Wang · 2021
Cited alongside, same era.
Dynamics randomization revisited: A case study for quadrupedal locomotion
Z. Xie, X. Da, M. Van de Panne, B. Babich, and A. Garg · 2021
Cited alongside, same era.
Rma: Rapid motor adaptation for legged robots
A. Kumar, Z. Fu, D. Pathak, and J. Malik · 2021
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D. Driess, F. Xia, M. S. Sajjadi, C. Lynch, A. Chowdhery, B. Ichter, A. Wahid, J. Tompson, Q. Vuong, T. Yu, et al · 2023
Later among the works it cites.
Barkour: Benchmarking animal-level agility with quadruped robots
K. Caluwaerts, A. Iscen, J. C. Kew, W. Yu, T. Zhang, D. Freeman, K.-H. Lee, L. Lee, S. Saliceti, V. Zhuang, et al · 2023
Later among the works it cites.
Robot parkour learning
Z. Zhuang, Z. Fu, J. Wang, C. G. Atkeson, S. Schwertfeger, C. Finn, and H. Zhao · 2023
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Extreme parkour with legged robots
X. Cheng, K. Shi, A. Agarwal, and D. Pathak · 2023
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Learning agile soccer skills for a bipedal robot with deep reinforcement learning
T. Haarnoja, B. Moran, G. Lever, S. H. Huang, D. Tirumala, M. Wulfmeier, J. Humplik, S. Tunyasuvunakool, N. Y. Siegel, R. Hafner, et al · 2023
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Walk these ways: Tuning robot control for generalization with multiplicity of behavior
G. B. Margolis and P. Agrawal · 2023
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Neural volumetric memory for visual locomotion control
R. Yang, G. Yang, and X. Wang · 2023
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Adapt on-the-go: Behavior modulation for single-life robot deployment
A. S. Chen, G. Chada, L. Smith, A. Sharma, Z. Fu, S. Levine, and C. Finn · 2023
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Code as policies: Language model programs for embodied control
J. Liang, W. Huang, F. Xia, P. Xu, K. Hausman, B. Ichter, P. Florence, and A. Zeng · 2023
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Progprompt: Generating situated robot task plans using large language models
I. Singh, V. Blukis, A. Mousavian, A. Goyal, D. Xu, J. Tremblay, D. Fox, J. Thomason, and A. Garg · 2023
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Language to rewards for robotic skill synthesis
W. Yu, N. Gileadi, C. Fu, S. Kirmani, K.-H. Lee, M. G. Arenas, H.-T. L. Chiang, T. Erez, L. Hasenclever, J. Humplik, et al · 2023
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Languagempc: Large language models as decision makers for autonomous driving
H. Sha, Y. Mu, Y. Jiang, L. Chen, C. Xu, P. Luo, S. E. Li, M. Tomizuka, W. Zhan, and M. Ding · 2023
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Large language models as general pattern machines
S. Mirchandani, F. Xia, P. Florence, B. Ichter, D. Driess, M. G. Arenas, K. Rao, D. Sadigh, and A. Zeng · 2023
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How to prompt your robot: A promptbook for manipulation skills with code as policies
M. G. Arenas, T. Xiao, S. Singh, V. Jain, A. Z. Ren, Q. Vuong, J. Varley, A. Herzog, I. Leal, S. Kirmani, et al · 2023
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Distilling and retrieving generalizable knowledge for robot manipulation via language corrections
L. Zha, Y. Cui, L.-H. Lin, M. Kwon, M. G. Arenas, A. Zeng, F. Xia, and D. Sadigh · 2023
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Voxposer: Composable 3d value maps for robotic manipulation with language models
W. Huang, C. Wang, R. Zhang, Y. Li, J. Wu, and L. Fei-Fei · 2023
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Saytap: Language to quadrupedal locomotion
Y. Tang, W. Yu, J. Tan, H. Zen, A. Faust, and T. Harada · 2023
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Agile but safe: Learning collision-free high-speed legged locomotion
T. He, C. Zhang, W. Xiao, G. He, C. Liu, and G. Shi · 2024
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Learning to learn faster from human feedback with language model predictive control
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Pivot: Iterative visual prompting elicits actionable knowledge for vlms
S. Nasiriany, F. Xia, W. Yu, T. Xiao, J. Liang, I. Dasgupta, A. Xie, D. Driess, A. Wahid, Z. Xu, et al · 2024
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Rt-h: Action hierarchies using language
S. Belkhale, T. Ding, T. Xiao, P. Sermanet, Q. Vuong, J. Tompson, Y. Chebotar, D. Dwibedi, and D. Sadigh · 2024
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Long-horizon locomotion and manipulation on a quadrupedal robot with large language models
Y. Ouyang, J. Li, Y. Li, Z. Li, C. Yu, K. Sreenath, and Y. Wu · 2024
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