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Humanoid robots require both robust lower-body locomotion and precise upper-body manipulation.
H. Miura and I. Shimoyama, “Dynamic walk of a biped,” IJRR , 1984
1984
Earlier work this paper cites.
S. Kajita, F. Kanehiro, K. Kaneko, K. Yokoi, and H. Hirukawa, “The 3d linear inverted pendulum mode: A simple modeling for a biped walking pattern generation,” in Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No. 01CH37180) , vol. 1. IEEE, 2001, pp. 239–246
2001
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.
K. Yin, K. Loken, and M. Van de Panne, “Simbicon: Simple biped locomotion control,” ACM Transactions on Graphics , 2007
2007
Earlier work this paper cites.
B. Dariush, M. Gienger, B. Jian, C. Goerick, and K. Fujimura, “Whole body humanoid control from human motion descriptors,” in 2008 IEEE International Conference on Robotics and Automation . IEEE, 2008, pp. 2677–2684
2008
Earlier work this paper cites.
M. Hutter, C. Gehring, D. Jud, A. Lauber, C. D. Bellicoso, V. Tsounis, J. Hwangbo, K. Bodie, P. Fankhauser, M. Bloesch et al. , “Anymal-a highly mobile and dynamic quadrupedal robot,” in IROS , 2016
2016
Earlier work this paper cites.
2017
Earlier work this paper cites.
N. Mahmood, N. Ghorbani, N. F. Troje, G. Pons-Moll, and M. J. Black, “Amass: Archive of motion capture as surface shapes,” in The IEEE International Conference on Computer Vision (ICCV) , Oct 2019. [Online]. Available: https://amass.is.tue.mpg.de
2019
Earlier work this paper cites.
F. L. Moro and L. Sentis, “Whole-body control of humanoid robots,” Humanoid Robotics: A reference, Springer, Dordrecht , 2019
2019
Earlier work this paper cites.
H. Y. Ling, F. Zinno, G. Cheng, and M. Van De Panne, “Character controllers using motion vaes,” ACM Transactions on Graphics (TOG) , vol. 39, no. 4, pp. 40–1, 2020
2020
Earlier work this paper cites.
D. Rempe, T. Birdal, A. Hertzmann, J. Yang, S. Sridhar, and L. J. Guibas, “Humor: 3d human motion model for robust pose estimation,” in International Conference on Computer Vision (ICCV) , 2021
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
Z. Fu, A. Kumar, J. Malik, and D. Pathak, “Minimizing energy consumption leads to the emergence of gaits in legged robots,” Conference on Robot Learning (CoRL) , 2021
2021
Earlier work this paper cites.
Z. Li, X. Cheng, X. B. Peng, P. Abbeel, S. Levine, G. Berseth, and K. Sreenath, “Reinforcement learning for robust parameterized locomotion control of bipedal robots,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. 2811–2817
2021
Earlier work this paper cites.
2021
Earlier work this paper cites.
X. B. Peng, Z. Ma, P. Abbeel, S. Levine, and A. Kanazawa, “Amp: Adversarial motion priors for stylized physics-based character control,” ACM Transactions on Graphics (ToG) , vol. 40, no. 4, pp. 1–20, 2021
2021
Earlier work this paper cites.
J. Fu, Y. Song, Y. Wu, F. Yu, and D. Scaramuzza, “Learning deep sensorimotor policies for vision-based autonomous drone racing,” 2022
2022
Cited alongside, same era.
2022
Cited alongside, same era.
A. Escontrela, X. B. Peng, W. Yu, T. Zhang, A. Iscen, K. Goldberg, and P. Abbeel, “Adversarial motion priors make good substitutes for complex reward functions. 2022 ieee,” in International Conference on Intelligent Robots and Systems (IROS) , vol. 2, 2022
2022
Cited alongside, same era.
Y. Ma, F. Farshidian, T. Miki, J. Lee, and M. Hutter, “Combining learning-based locomotion policy with model-based manipulation for legged mobile manipulators,” RA-L , 2022
2022
Cited alongside, same era.
2024
Closest in time.
2024
Closest in time.
X. Cheng, J. Li, S. Yang, G. Yang, and X. Wang, “Open-television: Teleoperation with immersive active visual feedback,” CoRL , 2024
2024
Closest in time.
Y. Park and P. Agrawal, “Using apple vision pro to train and control robots,” 2024. [Online]. Available: https://github.com/Improbable-AI/VisionProTeleop
2024
Closest in time.
M. Liu, Z. Chen, X. Cheng, Y. Ji, R. Qiu, R. Yang, and X. Wang, “Visual whole-body control for legged loco-manipulation,” CoRL , 2024
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X. B. Peng, Y. Guo, L. Halper, S. Levine, and S. Fidler, “Ase: Large-scale reusable adversarial skill embeddings for physically simulated characters,” ACM Trans. Graph. , vol. 41, no. 4, Jul. 2022
2022
Cited alongside, same era.
2023
Cited alongside, same era.
G. B. Margolis and P. Agrawal, “Walk these ways: Tuning robot control for generalization with multiplicity of behavior,” in Conference on Robot Learning . PMLR, 2023, pp. 22–31
2023
Cited alongside, same era.
2023
Cited alongside, same era.
X. Cheng, A. Kumar, and D. Pathak, “Legs as manipulator: Pushing quadrupedal agility beyond locomotion,” in 2023 IEEE International Conference on Robotics and Automation (ICRA) , 2023
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
M. Seo, S. Han, K. Sim, S. H. Bang, C. Gonzalez, L. Sentis, and Y. Zhu, “Deep imitation learning for humanoid loco-manipulation through human teleoperation,” in 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids) . IEEE, 2023, pp. 1–8
2023
Cited alongside, same era.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
C. Zhang, W. Xiao, T. He, and G. Shi, “Wococo: Learning whole-body humanoid control with sequential contacts,” arXiv e-prints , pp. arXiv–2406, 2024
2024
Closest in time.
2024
Closest in time.
T. He, Z. Luo, W. Xiao, C. Zhang, K. Kitani, C. Liu, and G. Shi, “Learning human-to-humanoid real-time whole-body teleoperation,” in arXiv , 2024
2024
Closest in time.
2024
Closest in time.
J. Dao, H. Duan, and A. Fern, “Sim-to-real learning for humanoid box loco-manipulation,” in 2024 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2024, pp. 16 930–16 936
2024
Closest in time.
Z. Luo, J. Cao, J. Merel, A. Winkler, J. Huang, K. M. Kitani, and W. Xu, “Universal humanoid motion representations for physics-based control,” in The Twelfth International Conference on Learning Representations , 2024. [Online]. Available: https://openreview.net/forum?id=OrOd8PxOO2
2024
Closest in time.
J. Wang, J. Hodgins, and J. Won, “Strategy and skill learning for physics-based table tennis animation,” in ACM SIGGRAPH 2024 Conference Papers , 2024, pp. 1–11
2024
Closest in time.