Zobrazeno 1 - 10
of 1 251
pro vyhledávání: '"Zhang, Hai‐tao"'
We design a distributed coordinated guiding vector field (CGVF) for a group of robots to achieve ordering-flexible motion coordination while maneuvering on a desired two-dimensional (2D) surface. The CGVF is characterized by three terms, i.e., a conv
Externí odkaz:
http://arxiv.org/abs/2401.14013
Autor:
Hu, Bin-Bin, Zhang, Hai-Tao, Liu, Bin, Ding, Jianing, Xu, Yifan, Luo, Chuanshang, Cao, Haosen
Publikováno v:
Published on IEEE Transactions on Control System Technology, 2023
This paper proposes a distributed guiding-vector-field (DGVF) controller for cross-domain unmanned systems (CDUSs) consisting of heterogeneous unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs), to achieve coordinated navigation whe
Externí odkaz:
http://arxiv.org/abs/2312.10946
Publikováno v:
Automatica, 2023
This paper proposes a label-free controller for a second-order multi-agent system to cooperatively fence a moving target of variational velocity into a convex hull formed by the agents whereas maintaining a rigid formation. Therein, no label is prede
Externí odkaz:
http://arxiv.org/abs/2311.00978
Publikováno v:
IEEE Transaction on Robotics, 2023
In this paper, we propose a distributed guiding-vector-field (DGVF) algorithm for a team of robots to form a spontaneous-ordering platoon moving along a predefined desired path in the n-dimensional Euclidean space. Particularly, by adding a path para
Externí odkaz:
http://arxiv.org/abs/2311.00976
In this paper, a Hankel matrix-based fully distributed algorithm is proposed to address a minimal-time deadbeat consensus prediction problem for discrete-time high-order multi-agent systems (MASs). Therein, each agent can predict the consensus value
Externí odkaz:
http://arxiv.org/abs/2304.06224
Publikováno v:
In Gene 15 January 2025 933
Publikováno v:
In Petroleum Science August 2024 21(4):2638-2649
Autor:
Gavidia, Marino, Zhu, Hongling, Montanari, Arthur N., Fuentes, Jesús, Cheng, Cheng, Dubner, Sergio, Chames, Martin, Maison-Blanche, Pierre, Rahman, Md Moklesur, Sassi, Roberto, Badilini, Fabio, Jiang, Yinuo, Zhang, Shengjun, Zhang, Hai-Tao, Du, Hao, Teng, Basi, Yuan, Ye, Wan, Guohua, Tang, Zhouping, He, Xin, Yang, Xiaoyun, Goncalves, Jorge
Publikováno v:
In Patterns 14 June 2024 5(6)
Autor:
Yuan, Ye, Liu, Jun, Jin, Dou, Yue, Zuogong, Chen, Ruijuan, Wang, Maolin, Sun, Chuan, Xu, Lei, Hua, Feng, He, Xin, Yi, Xinlei, Yang, Tao, Zhang, Hai-Tao, Sui, Shaochun, Ding, Han
Traditional machine learning relies on a centralized data pipeline, i.e., data are provided to a central server for model training. In many applications, however, data are inherently fragmented. Such a decentralized nature of these databases presents
Externí odkaz:
http://arxiv.org/abs/2107.07171
Autor:
Cao, Haosen, Hu, Bin-Bin, Mo, Xiaoyu, Chen, Duxin, Gao, Jianxi, Yuan, Ye, Chen, Guanrong, Vicsek, Tamás, Guan, Xiaohong, Zhang, Hai-Tao
Publikováno v:
In Engineering May 2024 36:240-249