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In this paper, a hierarchical and robust framework for learning bipedal locomotion is presented and successfully implemented on the 3D biped robot Digit built by Agility Robotics.
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M. Shafiee-Ashtiani, A. Yousefi-Koma, and M. Shariat-Panahi, “Robust bipedal locomotion control based on model predictive control and divergent component of motion,” in 2017 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2017, pp. 3505–3510
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H. Chen, B. Wang, Z. Hong, C. Shen, P. M. Wensing, and W. Zhang, “Underactuated motion planning and control for jumping with wheeled-bipedal robots,” IEEE Robotics and Automation Letters , 2020
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G. A. Castillo, B. Weng, W. Zhang, and A. Hereid, “Hybrid zero dynamics inspired feedback control policy design for 3d bipedal locomotion using reinforcement learning,” in 2020 IEEE International Conference on Robotics and Automation (ICRA) , 2020, pp. 8746–8752
2020
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2019
Cited alongside, same era.
T. Li, H. Geyer, C. G. Atkeson, and A. Rai, “Using deep reinforcement learning to learn high-level policies on the atrias biped,” in 2019 International Conference on Robotics and Automation (ICRA) . IEEE, 2019, pp. 263–269
2019
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2019
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J. Hurst, “Building Robots That Can Go Where We Go,” IEEE Spectrum: Technology, Engineering, and Science News , Feb. 2019. [Online]. Available: https://spectrum.ieee.org/robotics/humanoids/building-robots-that-can-go-where-we-go
2019
Cited alongside, same era.
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,” American Control Conference (ACC) , 2019
2019
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J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter, “Learning quadrupedal locomotion over challenging terrain,” Science robotics , vol. 5, no. 47, 2020
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2020
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“Robust Feedback Motion Policy Design Using Reinforcement Learning on a 3D Digit Bipedal Robot,” https://youtu.be/j8KbW-a9dbw, accessed: 2021-03-29
2021
Closest in time.