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In this work, we propose a learning approach for 3D dynamic bipedal walking when footsteps are constrained to stepping stones.
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Q. Nguyen, A. Hereid, J. W. Grizzle, A. D. Ames, and K. Sreenath, “3d dynamic walking on stepping stones with control barrier functions,” in 2016 IEEE 55th Conference on Decision and Control (CDC) , 2016, pp. 827–834
2016
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S. Garrido-Jurado, R. Muñoz-Salinas, F. J. Madrid-Cuevas, and R. Medina-Carnicer, “Generation of fiducial marker dictionaries using Mixed Integer Linear Programming,” Pattern Recognition , vol. 51, no. October 2017, pp. 481–491, 2016
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Q. Nguyen, A. Agrawal, X. Da, W. C. Martin, H. Geyer, J. W. Grizzle, and K. Sreenath, “Dynamic walking on randomly-varying discrete terrain with one-step preview,” Robotics: Science and Systems , vol. 13, 2017
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2018
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F. J. Romero-Ramirez, R. Muñoz-Salinas, and R. Medina-Carnicer, “Speeded up detection of squared fiducial markers,” Image and Vision Computing , vol. 76, no. June, pp. 38–47, 2018
2018
Cited alongside, same era.
Q. Nguyen, X. Da, J. W. Grizzle, and K. Sreenath, “Dynamic Walking on Stepping Stones with Gait Library and Control Barrier Functions,” in Springer Proceedings in Advanced Robotics , 2020, vol. 13, pp. 384–399
2020
Cited alongside, same era.
Z. Xie, H. Y. Ling, N. H. Kim, and M. Van De Panne, “ALLSTEPS: Curriculum-driven learning of stepping stone skills,” ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA 2020 , vol. 39, no. 8, pp. 213–224, 2020
2020
Cited alongside, same era.
V. Tsounis, M. Alge, J. Lee, F. Farshidian, and M. Hutter, “Deepgait: Planning and control of quadrupedal gaits using deep reinforcement learning,” IEEE Robotics and Automation Letters , vol. 5, no. 2, pp. 3699–3706, 2020
2020
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
Later among the works it cites.
2021
Later among the works it cites.
W. Yu, D. Jain, A. Escontrela, and A. Iscen, “Visual-Locomotion : Learning to Walk on Complex Terrains with Vision,” 5th Conference on Robot Learning (CoRL 2021) , no. CoRL 2021, pp. 1–12, 2021
2021
Later among the works it cites.
J. Siekmann, K. Green, J. Warila, A. Fern, and J. Hurst, “Blind Bipedal Stair Traversal via Sim-to-Real Reinforcement Learning,” 2021
2021
Later among the works it cites.
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J. Siekmann, S. Valluri, J. Dao, F. Bermillo, H. Duan, A. Fern, and J. Hurst, “Learning Memory-Based Control for Human-Scale Bipedal Locomotion,” in Proceedings of Robotics: Science and Systems , Corvalis, Oregon, USA, July 2020
2020
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Cited alongside, same era.
L. Krishna, G. A. Castillo, U. A. Mishra, A. Hereid, and S. Kolathaya, “Linear Policies are Sufficient to Realize Robust Bipedal Walking on Challenging Terrains,” IEEE Robotics and Automation Letters , vol. 7, no. 2, pp. 2047–2054, 2022
2022
Closest in time.
G. B. Margolis, T. Chen, K. Paigwar, X. Fu, D. Kim, S. b. Kim, and P. Agrawal, “Learning to jump from pixels,” in Proceedings of the 5th Conference on Robot Learning , ser. Proceedings of Machine Learning Research, A. Faust, D. Hsu, and G. Neumann, Eds., vol. 164. PMLR, 08–11 Nov 2022, pp. 1025–1034. [Online]. Available: https://proceedings.mlr.press/v164/margolis22a.html
2022
Closest in time.
H. Duan, A. Malik, J. Dao, A. Saxena, K. Green, J. Siekmann, A. Fern, and J. Hurst, “Sim-to-Real Learning of Footstep-Constrained Bipedal Dynamic Walking,” in accepted to IEEE International Conference on Robotics and Automation, 2022 , 2022
2022
Closest in time.