3D point cloud capture method for underwater structures in turbid environment

Abstract

Abstract Underwater structure inspections are essential for infrastructure maintenance, such as hydraulic facilities, bridges, and ports. Due to the influence of turbidity, dark light, and distortion, the traditional methods cannot satisfy the requirements of on-site inspection applications. This paper proposed a methodology of the point cloud data capture in the turbid underwater environment. The method consisted of an acquisition device, a distortion correction algorithm, and a parameter optimization approach. The acquisition device was designed by composing a silt-removing module, a structured light camera module, and a clear water replacement module, which can integrate with an underwater inspection robot. The underwater multi-medium plane refraction distortion model was established through analysis, and a refraction correction algorithm was provided to correct the distortion. To obtain the maximum field of view of the point cloud, the nonlinear optimization approach was used to select the medium material and thickness. After the real experiments using the Intel RealSense sr300 depth camera, maximum measuring distance could range up to 253 mm in water, the accuracy of the point cloud of the underwater target objects was ±3.77 mm, and the maximum error was 8.76%. Compared with other methods, this method was more suitable for 3D point cloud capture in the turbidity environment.