YOLOX-DG robotic detection systems for large-scale underwater concrete structures

Chenjie Zhang; Hongkuan Ma; Zhaochang Chen; Shengquan Li; Zhongze Ma; Hui Huang; Ronghua Zhu; Pengcheng Jiao

doi:10.1016/j.isci.2024.109337

YOLOX-DG robotic detection systems for large-scale underwater concrete structures

iScience. 2024 Feb 28;27(4):109337. doi: 10.1016/j.isci.2024.109337. eCollection 2024 Apr 19.

Authors

Chenjie Zhang¹, Hongkuan Ma¹, Zhaochang Chen¹, Shengquan Li^{1

2}, Zhongze Ma¹, Hui Huang^{1

2}, Ronghua Zhu¹, Pengcheng Jiao^{1

3

2}

Affiliations

¹ Ocean College, Zhejiang University, Zhoushan, Zhejiang 316021, China.
² Hainan Institute of Zhejiang University, Sanya, Hainan 572025, China.
³ Engineering Research Center of Oceanic Sensing Technology and Equipment, Zhejiang University, Ministry of Education, Hangzhou, Zhejiang, China.

Abstract

Large-scale complex underwater concrete structures have structural damage and the traditional damage detection method mostly uses manual identification, which is inaccurate and inefficient. Therefore, robotic detection systems have been proposed to replace manual identification for underwater concrete structures in ocean engineering. However, the highly corrosive and disruptive environment of the ocean poses great difficulties for the application. Here, we develop a manta ray-inspired underwater robot with well controllability to establish the damage datasets of underwater concrete structures, proposing the YOLOX-DG algorithm to improve the damage detection accuracy, and integrating the model into the robotic detection systems for underwater concrete damages. Eventually, the system is used for ocean testing in real applications (i.e., underwater marine harbors around the East China Sea), and satisfactory detection performance is obtained. The reported manta ray-inspired robotic detection system can be used to accurately monitor and analyze the underwater regions.

Keywords: Artificial intelligence; Engineering; Robotics.