Author:
Wei Lang,Zou Jinzhou,Yu Xi,Liu Liangyu,Liao Jianbin,Wang Wei,Zhang Tong
Publisher
Springer Science and Business Media LLC
Reference27 articles.
1. Xu, J., Tian, Y., Ma, P., Rus, D., Sueda, S., & Matusik, W. (2020). Prediction-guided multi-objective reinforcement learning for continuous robot control. In International conference on machine learning, Vienna, Austria (pp. 10607–10616).
2. Alexander, R. M. (1984). The gaits of bipedal and quadrupedal animals. The International Journal of Robotics Research, 3(2), 49–59.
3. Xi, W., Yesilevskiy, Y., & Remy, C. D. (2016). Selecting gaits for economical locomotion of legged robots. The International Journal of Robotics Research, 35(9), 1140–1154.
4. Polet, D. T., & Bertram, J. E. (2019). An inelastic quadrupedal model discovers four-beat walking, two-beat running, and pseudo-elastic actuation as energetically optimal. PLoS Computational Biology, 15(11), e1007444.
5. Peng, X. B., Berseth, G., Yin, K., & Van De Panne, M. (2017). Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement learning. ACM Transactions on Graphics (TOG), 36(4), 1–13.