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pro vyhledávání: '"Zeng, Xuanqi"'
Model Predictive Control (MPC) relies heavily on the robot model for its control law. However, a gap always exists between the reduced-order control model with uncertainties and the real robot, which degrades its performance. To address this issue, w
Externí odkaz:
http://arxiv.org/abs/2407.10124
Autor:
Yue, Linzhu, Zhang, Lingwei, Song, Zhitao, Zhang, Hongbo, Dong, Jinhu, Zeng, Xuanqi, Liu, Yun-Hui
Exploring the limits of quadruped robot agility, particularly in the context of rapid and real-time planning and execution of omnidirectional jump trajectories, presents significant challenges due to the complex dynamics involved, especially when con
Externí odkaz:
http://arxiv.org/abs/2407.00658
Offline evolutionary-based methodologies have supplied a successful motion planning framework for the quadrupedal jump. However, the time-consuming computation caused by massive population evolution in offline evolutionary-based jumping framework sig
Externí odkaz:
http://arxiv.org/abs/2309.07633
Akademický článek
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Publikováno v:
Proceedings of SPIE; 4/20/2023, Vol. 12507, p1250721-1250721, 1p
Publikováno v:
Proceedings of SPIE; 5/14/2022, Vol. 12166, p1216674-1216674, 1p
Autor:
Zhang, Xuejun, Sun, Hongbo, Fu, Yuegang, Kong, Lingbao, Zhang, Dawei, Xue, Donglin, Xue, Changxi, Zeng, Xuanqi, Zhang, Kaiyu, Liu, Xing, Liu, Peng, Weng, Tsu-chien
Publikováno v:
Proceedings of SPIE; January 2023, Vol. 12507 Issue: 1 p1250721-1250721-6