@inproceedings{1e6c7b402ced402b8ca5aeba17f7b9fb,
title = "A Positioning Method Based on Kalman Filter for FAST Feed Support Cable Inspection Robot",
abstract = "In this paper, a positioning system developed for cable inspection robot system which works on feed support cables of Five-hundred-meter Aperture Spherical radio Telescope (FAST) is introduced. The positioning system consists of wheeled odometers and a Real-tme kinematic (RTK) based Global Navigation Satellite System (GNSS). Firstly, the cable with fixed ends and free suspension in the middle is modeled, and the influence of wind on the cable in FAST site is analyzed. Then, the data of the four odometers on the robot are processed, and the odometer information is fused with GNSS information through Kalman filtering. Then the best position estimation of the cable inspection robot is determined. A simulation is finally established to verify the proposed robot positioning method. The result shows that the method can work pretty well under the real working situation.",
keywords = "GNSS, Kalman filter, inspection robot, odometer, positioning",
author = "Xiangyu Sun and Gangfeng Liu and Xuehe Zhang and Changle Li and Jie Zhao",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 9th International Conference on Mechatronics and Robotics Engineering, ICMRE 2023 ; Conference date: 10-02-2023 Through 12-02-2023",
year = "2023",
doi = "10.1109/ICMRE56789.2023.10106594",
language = "英语",
series = "2023 9th International Conference on Mechatronics and Robotics Engineering, ICMRE 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "65--71",
editor = "Yongsheng Ma",
booktitle = "2023 9th International Conference on Mechatronics and Robotics Engineering, ICMRE 2023",
address = "美国",
}