A novel localization approach for underwater welding vehicles in spent fuel pools via attitude heading reference system and altimeters

Author:

Luo Yang1ORCID,Tao Jianguo1,Sun Hao2,Hao Zhuang3,Li Hao1,Na Qiang1,Gao Haibo1,Ding Liang1,Deng Zongquan1

Affiliation:

1. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China

2. Department of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, China

3. Key Laboratory of Micro-systems and Micro-structures Manufacturing (Ministry of Education), Harbin Institute of Technology, Harbin, China

Abstract

In this article, a novel localization approach incorporating attitude and heading reference system and underwater altimeters is presented to accurately localize the underwater welding vehicles in spent fuel pools of the nuclear power stations. Different from the conventional underwater localization technologies, the presented localization approach is a more suitable approach in cases of confined structured water areas. Firstly, a multi-regions division localization algorithm is proposed for calculating the coordinate of the underwater welding vehicle through data from sensors. Also, considering the attitude errors of the underwater welding vehicle, the beam angle of the altimeters, and the boundary effects of cross-regions, an optimized multi-regions division localization algorithm is introduced for general applicability of the multi-regions division localization. Then, computer simulations are employed to evaluate the validity and the performance of multi-regions division localization and optimized multi-regions division localization. Finally, the efficiency of the proposed approach is confirmed via system experiments. The experimental results are consistent with simulation results which further indicate that the presented approach holds great potential in effective underwater vehicles localization for confined structured water scenarios.

Funder

National Key Basic Research Development Plan Project

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

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