Zobrazeno 1 - 10
of 103
pro vyhledávání: '"Lang, Haoxiang"'
Autor:
Ye, Zirong1,2 (AUTHOR), Lang, Haoxiang1,2 (AUTHOR), Xie, Zishan3 (AUTHOR), Duan, Siyu1,2 (AUTHOR), Peng, Bihao4,5 (AUTHOR), Chen, Xiaochun4,5 (AUTHOR), Fang, Ya1,2 (AUTHOR) fangya@xmu.edu.cn, Xin, Jiawei4,5 (AUTHOR) xinjw@fjmu.edu.cn
Publikováno v:
BMC Medicine. 9/30/2024, Vol. 22 Issue 1, p1-14. 14p.
Autonomous driving has been among the most popular and challenging topics in the past few years. On the road to achieving full autonomy, researchers have utilized various sensors, such as LiDAR, camera, Inertial Measurement Unit (IMU), and GPS, and d
Externí odkaz:
http://arxiv.org/abs/2206.05400
Publikováno v:
In Journal of Affective Disorders 15 January 2025 369:696-705
This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a 4-wheel skid-steer mobile robotic system. An LG representation of the system is proposed and the accompanying state-spa
Externí odkaz:
http://arxiv.org/abs/2110.00323
This paper proposes a methodology of integrating the Linear Graph (LG) approach with Genetic Programming (GP) for generating an automated multi-domain engineering design approach by using the in-house developed LG MATLAB toolbox and the GP toolbox in
Externí odkaz:
http://arxiv.org/abs/2109.12388
Publikováno v:
In Journal of Environmental Psychology December 2023 92
Publikováno v:
In Engineering Applications of Artificial Intelligence June 2023 122
Publikováno v:
In Journal of Energy Storage 1 December 2021 44 Part A
Autor:
Lang, Haoxiang
This thesis addresses the manipulation control of a mobile robot with the support of a sensor network, for carrying out dynamically challenging tasks. Such tasks are defined as those where the robot is required to first identify objects, approach and
Externí odkaz:
http://hdl.handle.net/2429/43277
Autor:
Lang, Haoxiang
Fault detection and diagnosis is quite important in engineering systems, and deserves further attention in view of the increasing complexity of modern machinery. Traditional single-sensor methods of fault monitoring and diagnosis may find it difficul
Externí odkaz:
http://hdl.handle.net/2429/891