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Accurate state estimation plays a critical role in ensuring the robust control of humanoid robots, particularly in the context of learning-based control policies for legged robots.
M. H. Raibert, Legged robots that balance . MIT press, 1986
1986
Earlier work this paper cites.
E. R. Westervelt, J. W. Grizzle, and D. E. Koditschek, “Hybrid zero dynamics of planar biped walkers,” IEEE transactions on automatic control , vol. 48, no. 1, pp. 42–56, 2003
2003
Earlier work this paper cites.
S. Collins, A. Ruina, R. Tedrake, and M. Wisse, “Efficient bipedal robots based on passive-dynamic walkers,” Science , vol. 307, no. 5712, pp. 1082–1085, 2005
2005
Earlier work this paper cites.
H. Herr and M. Popovic, “Angular momentum in human walking,” Journal of Experimental Biology , vol. 211, no. 4, pp. 467–481, feb 2008. [Online]. Available: https://doi.org/10.1242/jeb.008573
2008
Earlier work this paper cites.
S. Kuindersma, R. Deits, M. Fallon, A. Valenzuela, H. Dai, F. Permenter, T. Koolen, P. Marion, and R. Tedrake, “Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot,” Autonomous robots , vol. 40, pp. 429–455, 2016
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
I. Clavera, J. Rothfuss, J. Schulman, Y. Fujita, T. Asfour, and P. Abbeel, “Model-based reinforcement learning via meta-policy optimization,” in Conference on Robot Learning . PMLR, 2018, pp. 617–629
2018
Earlier work this paper cites.
J. Hwangbo, J. Lee, and M. Hutter, “Per-contact iteration method for solving contact dynamics,” IEEE Robotics and Automation Letters , vol. 3, no. 2, pp. 895–902, 2018
2018
Earlier work this paper cites.
Y. Gong, R. Hartley, X. Da, A. Hereid, O. Harib, J.-K. Huang, and J. Grizzle, “Feedback control of a cassie bipedal robot: Walking, standing, and riding a segway,” in 2019 American Control Conference (ACC) , 2019, pp. 4559–4566
2019
Earlier work this paper cites.
J. Reher, W.-L. Ma, and A. D. Ames, “Dynamic walking with compliance on a cassie bipedal robot,” in 2019 18th European Control Conference (ECC) , 2019, pp. 2589–2595
2019
Earlier work this paper cites.
J. Hwangbo, J. Lee, A. Dosovitskiy, D. Bellicoso, V. Tsounis, V. Koltun, and M. Hutter, “Learning agile and dynamic motor skills for legged robots,” Science Robotics , vol. 4, no. 26, p. eaau5872, Jan 2019
2019
Earlier work this paper cites.
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Köpf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala, “Pytorch: An imperative style, high-performance deep learning library,” in 33rd International Conference on Neural Information Processing Systems (NIPS) . Red Hook, NY, USA: Curran Associates Inc., 2019, pp. 1–12
2019
Earlier work this paper cites.
J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter, “Learning quadrupedal locomotion over challenging terrain,” Science robotics , vol. 5, no. 47, p. eabc5986, 2020
2020
Earlier work this paper cites.
C. Yang, K. Yuan, Q. Zhu, W. Yu, and Z. Li, “Multi-expert learning of adaptive legged locomotion,” Science Robotics , vol. 5, no. 49, p. eabb2174, 2020
2020
Cited alongside, same era.
A. Kumar, Z. Fu, D. Pathak, and J. Malik, “RMA: rapid motor adaptation for legged robots,” in Robotics: Science and Systems (RSS) , 2021
2021
Cited alongside, same era.
J. Siekmann, Y. Godse, A. Fern, and J. Hurst, “Sim-to-real learning of all common bipedal gaits via periodic reward composition,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) , 2021, pp. 7309–7315
2021
Cited alongside, same era.
J. Siekmann, K. Green, J. Warila, A. Fern, and J. Hurst, “Blind bipedal stair traversal via sim-to-real reinforcement learning,” in Robotics: Science and Systems (RSS) , ser. Robotics - Science and Systems, 2021
2021
Cited alongside, same era.
R. Batke, F. Yu, J. Dao, J. Hurst, R. L. Hatton, A. Fern, and K. Green, “Optimizing bipedal maneuvers of single rigid-body models for reinforcement learning,” in 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) . IEEE, 2022, pp. 714–721
2022
Later among the works it cites.
Z. Wang, W. Wei, A. Xie, Y. Zhang, J. Wu, and Q. Zhu, “Hybrid bipedal locomotion based on reinforcement learning and heuristics,” MICROMACHINES , vol. 13, no. 10, OCT 2022
2022
Later among the works it cites.
G. Ji, J. Mun, H. Kim, and J. Hwangbo, “Concurrent training of a control policy and a state estimator for dynamic and robust legged locomotion,” IEEE Robotics and Automation Letters , vol. 7, no. 2, pp. 4630–4637, 2022
2022
Later among the works it cites.
J.-K. Huang and J. W. Grizzle, “Efficient anytime clf reactive planning system for a bipedal robot on undulating terrain,” IEEE Transactions on Robotics , vol. 39, no. 3, pp. 2093–2110, 2023
2023
Later among the works it cites.
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V. Makoviychuk, L. Wawrzyniak, Y. Guo, M. Lu, K. Storey, M. Macklin, D. Hoeller, N. Rudin, A. Allshire, A. Handa, and G. State, “Isaac gym: High performance gpu-based physics simulation for robot learning,” 2021
2021
Cited alongside, same era.
G. Gibson, O. Dosunmu-Ogunbi, Y. Gong, and J. Grizzle, “Terrain-adaptive, alip-based bipedal locomotion controller via model predictive control and virtual constraints,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2022, pp. 6724–6731
2022
Cited alongside, same era.
T. Miki, J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter, “Learning robust perceptive locomotion for quadrupedal robots in the wild,” Science Robotics , vol. 7, no. 62, p. eabk2822, 2022
2022
Cited alongside, same era.
G. B. Margolis and P. Agrawal, “Walk these ways: tuning robot control for generalization with multiplicity of behavior,” Conference on Robot Learning (CoRL) , 2022
2022
Cited alongside, same era.
G. Margolis, G. Yang, K. Paigwar, T. Chen, and P. Agrawal, “Rapid locomotion via reinforcement learning,” in Robotics: Science and Systems (RSS) , 2022
2022
Cited alongside, same era.
A. Agarwal, A. Kumar, J. Malik, and D. Pathak, “Legged locomotion in challenging terrains using egocentric vision,” in 6th Annual Conference on Robot Learning (CoRL) , 2022. [Online]. Available: https://openreview.net/forum?id=Re3NjSwf0WF
2022
Cited alongside, same era.
A. Kumar, Z. Li, J. Zeng, D. Pathak, K. Sreenath, and J. Malik, “Adapting rapid motor adaptation for bipedal robots,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , oct 2022, pp. 1161–1168, iSSN: 2153-0866
2022
Cited alongside, same era.
H. Duan, A. Malik, M. S. Gadde, J. Dao, A. Fern, and J. Hurst, “Learning dynamic bipedal walking across stepping stones,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , ser. IEEE International Conference on Intelligent Robots and Systems, 2022, pp. 6746–6752
2022
Cited alongside, same era.
2023
Later among the works it cites.
B. Dynamics, “Picking up momentum,” 2023. [Online]. Available: https://www.bostondynamics.com/resources/blog/picking-momentum
2023
Later among the works it cites.
A. Loquercio, A. Kumar, and J. Malik, “Learning visual locomotion with cross-modal supervision,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 7295–7302
2023
Later among the works it cites.
I. M. A. Nahrendra, B. Yu, and H. Myung, “Dreamwaq: Learning robust quadrupedal locomotion with implicit terrain imagination via deep reinforcement learning,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2023, pp. 5078–5084
2023
Later among the works it cites.
2023
Later among the works it cites.
2023
Later among the works it cites.
J. Bastien and L. Birglen, “Power efficient design a compliant robotic leg based on klann’s linkage,” IEEE/ASME Transactions on Mechatronics , vol. 28, no. 2, pp. 814–824, 2023
2023
Later among the works it cites.
W. Wei, Z. Wang, A. Xie, J. Wu, R. Xiong, and Q. Zhu, “Learning gait-conditioned bipedal locomotion with motor adaptation*,” in 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids) , 2023, pp. 1–7
2023
Later among the works it cites.