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Quadruped animals are capable of exhibiting a diverse range of locomotion gaits.
Highly dynamic quadruped locomotion via whole-body impulse control and model predictive control
Kim, D.; Di Carlo, J.; Katz, B.; Bledt, G.; and Kim, S. 2019 · 1909
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Gait and the energetics of locomotion in horses
Hoyt, D. F.; and Taylor, C. R. 1981 · 1981
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Learning agile robotic locomotion skills by imitating animals
Peng, X. B.; Coumans, E.; Zhang, T.; Lee, T.-W.; Tan, J.; and Levine, S. 2020 · 2004
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Reward machines for cooperative multi-agent reinforcement learning
Neary, C.; Xu, Z.; Wu, B.; and Topcu, U. 2020 · 2007
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Sim-to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition
Siekmann, J.; Godse, Y.; Fern, A.; and Hurst, J. 2020 · 2011
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Proximal policy optimization algorithms
Schulman, J.; Wolski, F.; Dhariwal, P.; Radford, A.; and Klimov, O. 2017 · 2017
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Diverse exploration for fast and safe policy improvement
Cohen, A.; Yu, L.; and Wright, R. 2018 · 2018
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Dynamic locomotion in the mit cheetah 3 through convex model-predictive control
Di Carlo, J.; Wensing, P. M.; Katz, B.; Bledt, G.; and Kim, S. 2018 · 2018
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Using reward machines for high-level task specification and decomposition in reinforcement learning
Icarte, R. T.; Klassen, T.; Valenzano, R.; and McIlraith, S. 2018 · 2018
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Policies modulating trajectory generators
Iscen, A.; Caluwaerts, K.; Tan, J.; Zhang, T.; Coumans, E.; Sindhwani, V.; and Vanhoucke, V. 2018 · 2018
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Sim-to-real: Learning agile locomotion for quadruped robots
Tan, J.; Zhang, T.; Coumans, E.; Iscen, A.; Bai, Y.; Hafner, D.; Bohez, S.; and Vanhoucke, V. 2018 · 2018
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Learning reward machines for partially observable reinforcement learning
Toro Icarte, R.; Waldie, E.; Klassen, T.; Valenzano, R.; Castro, M.; and McIlraith, S. 2019 · 2019
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Joint inference of reward machines and policies for reinforcement learning
Xu, Z.; Gavran, I.; Ahmad, Y.; Majumdar, R.; Neider, D.; Topcu, U.; and Wu, B. 2020 · 2020
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Reward machines for vision-based robotic manipulation
Camacho, A.; Varley, J.; Zeng, A.; Jain, D.; Iscen, A.; and Kalashnikov, D. 2021 · 2021
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Learning a contact-adaptive controller for robust, efficient legged locomotion
Da, X.; Xie, Z.; Hoeller, D.; Boots, B.; Anandkumar, A.; Zhu, Y.; Babich, B.; and Garg, A. 2021 · 2021
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Minimizing energy consumption leads to the emergence of gaits in legged robots
Fu, Z.; Kumar, A.; Malik, J.; and Pathak, D. 2021 · 2021
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Reward machines: Exploiting reward function structure in reinforcement learning
Icarte, R. T.; Klassen, T. Q.; Valenzano, R.; and McIlraith, S. A. 2022 · 2022
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Concurrent training of a control policy and a state estimator for dynamic and robust legged locomotion
Ji, G.; Mun, J.; Kim, H.; and Hwangbo, J. 2022 · 2022
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Learning robust perceptive locomotion for quadrupedal robots in the wild
Miki, T.; Lee, J.; Hwangbo, J.; Wellhausen, L.; Koltun, V.; and Hutter, M. 2022 · 2022
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Learning to walk in minutes using massively parallel deep reinforcement learning
Rudin, N.; Hoeller, D.; Reist, P.; and Hutter, M. 2022 · 2022
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Fast and efficient locomotion via learned gait transitions
Yang, Y.; Zhang, T.; Coumans, E.; Tan, J.; and Boots, B. 2022 · 2022
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Seeing-Eye Quadruped Navigation with Force Responsive Locomotion Control
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Kumar, A.; Fu, Z.; Pathak, D.; and Malik, J. 2021 · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
Makoviychuk, V.; Wawrzyniak, L.; Guo, Y.; Lu, M.; Storey, K.; Macklin, M.; Hoeller, D.; Rudin, N.; Allshire, A.; Handa, A.; et al. 2021 · 2021
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Learning free gait transition for quadruped robots via phase-guided controller
Shao, Y.; Jin, Y.; Liu, X.; He, W.; Wang, H.; and Yang, W. 2021 · 2021
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Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
Smith, L.; Kew, J. C.; Peng, X. B.; Ha, S.; Tan, J.; and Levine, S. 2021 · 2021
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Multi-Agent Intention Progression with Reward Machines
Dann, M.; Yao, Y.; Alechina, N.; Logan, B.; Thangarajah, J.; et al. 2022 · 2022
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Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning
Dohmen, T.; Topper, N.; Atia, G.; Beckus, A.; Trivedi, A.; and Velasquez, A. 2022 · 2022
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DeFazio, D.; Hirota, E.; and Zhang, S. 2023 · 2023
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Walk these ways: Tuning robot control for generalization with multiplicity of behavior
Margolis, G. B.; and Agrawal, P. 2023 · 2023
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SayTap: Language to Quadrupedal Locomotion
Tang, Y.; Yu, W.; Tan, J.; Zen, H.; Faust, A.; and Harada, T. 2023 · 2023
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Language to Rewards for Robotic Skill Synthesis
Yu, W.; Gileadi, N.; Fu, C.; Kirmani, S.; Lee, K.-H.; Arenas, M. G.; Chiang, H.-T. L.; Erez, T.; Hasenclever, L.; Humplik, J.; et al. 2023 · 2023
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Zhuang, Z.; Fu, Z.; Wang, J.; Atkeson, C.; Schwertfeger, S.; Finn, C.; and Zhao, H. 2023 · 2023
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