Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Zhaobing Kang"'
Publikováno v:
International Journal of Control, Automation and Systems. 20:1605-1620
Publikováno v:
International Journal of Control, Automation and Systems. 19:3785-3800
In visual servoing tasks, it is an important problem to maintain the observability to feature points on objects, which are usually used to calculate the pose between objects and robots. In particular, when the robot’s vision has a limited field of
Autor:
Wei Zou, Zhaobing Kang
Publikováno v:
Advanced Robotics. 34:1272-1278
This paper aims to correct camera pose estimation results acquired by bundle adjustment (BA) optimization in visual-inertial SLAM (VI-SLAM) approaches. By deriving the relationship between the pose...
Publikováno v:
International Journal of Automation and Computing. 17:267-278
This paper presents a two-stage smooth-optimal trajectory tracking strategy. Different from existing methods, the optimal trajectory tracked point can be directly determined in an uncalibrated fish-eye image. In the first stage, an adaptive trajector
Publikováno v:
International Journal of Automation and Computing. 16:761-774
In this paper, we propose a method to select the observation position in visual servoing with an eye-in-vehicle configuration for the manipulator. In traditional visual servoing, the images taken by the camera may have various problems, including bei
Publikováno v:
International Journal of Control, Automation and Systems. 17:2297-2309
This paper presents a novel adaptive trajectory tracking control method, which can precisely control wheeled mobile robots only using an uncalibrated fish-eye camera fixed on the ceiling. Different from existing approaches, the inertial device, disto
Autor:
Guozhong Luo, Zilong Huang, Radu Timofte, Kwanggyoon Seo, Jialei Xu, Xingyi Li, Min Shi, Chuannan Sheng, Ang Li, Yang Liu, Tianpeng Feng, Bin Fu, Junjun Jiang, Jiaoyang Yao, Ziyu Zhang, Jung Eun Yoo, Grigory Malivenko, Yiran Wang, Wei-Chi Chen, Samarth Shukla, Andrey Ignatov, Shayan Joya, Zhiguo Cao, Ke Xian, Jian Yin, David Plowman, Xianming Liu, Gang Yu, Chao Ge, Jin-Hua Du, Bo Li, Zhenyu Li, Yicheng Wang, Huanhuan Fan, Zhaobing Kang, Fangwen Tu, Fausto T. Benavides, Pei-Lin Wu
Publikováno v:
CVPR Workshops
Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually very computationally expensive and thus are not applicable for on-dev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::761208b6a56bb0efd08830ccf7e5e14c