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基于语义分割和双目视觉的水下机器人测距技术研究

Research on underwater robot ranging technology based on semantic segmentation and binocular vision.

作者信息

Hu Qing, Wang Kekuan, Ren Fushen, Wang Zhongyang

机构信息

Sanya Offshore Oil and Gas Research Institute, Northeast Petroleum University, Sanya, 572025, China.

CNPC Engineering Technology Research Company Limited, Tianjin, 300451, China.

出版信息

Sci Rep. 2024 May 29;14(1):12309. doi: 10.1038/s41598-024-63017-8.

Abstract

Based on the principle of light refraction and binocular ranging, the underwater imaging model is obtained. It provides a theoretical basis for underwater camera calibration. In order to meet the requirement of underwater vehicle to identify and distance underwater target, a new underwater vehicle distance measurement system based on semantic segmentation and binocular vision is proposed. The system uses Deeplabv3 + to identify the underwater target captured by the binocular camera and generate the target map, which is then used for binocular ranging. Compared with the binocular ranging using the original drawing, the measurement accuracy of the proposed method has not changed, the measurement speed is increased by 30%, and the error rate is controlled within 5%, which meets the needs of underwater robot operations.

摘要

基于光折射原理和双目测距原理,得到水下成像模型。它为水下相机标定提供了理论依据。为满足水下航行器识别和测量水下目标距离的需求,提出了一种基于语义分割和双目视觉的新型水下航行器测距系统。该系统使用Deeplabv3+识别双目相机捕获的水下目标并生成目标地图,然后用于双目测距。与使用原始图像进行双目测距相比,该方法的测量精度不变,测量速度提高了30%,错误率控制在5%以内,满足了水下机器人作业的需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1653/11637160/909207f4c264/41598_2024_63017_Fig1_HTML.jpg

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