针对深海环境下通过视觉方法难以实现地貌的大范围、高精度三维重建的问题, 提出一种基于“蛟龙号”载人潜水器的线结构光法深海地貌三维重建视觉传感器的设计方案。根据线结构光三维重建的原理, 首先改进了Steger算法, 实现了快速、精准的激光条纹中心线提取; 然后利用直接标定法求解出地形特征的二维空间坐标, 并克服了图像畸变对重建的影响; 再将获得的二维点云与多传感器数据融合, 跟随潜水器坐标实时计算偏移量, 并根据传感器位姿变化对图像矫正, 最终获得地貌的三维点云数据。根据重建原理设计了视觉传感器的软硬件系统, 并搭建了实验模拟平台来验证方案的可行性。通过水下实验可以实现对模拟地貌的完整重建, 精度达到96.9%, 符合重建要求。

Aiming at the problem that it was difficult to achieve large-scale and high-precision 3D reconstruction of land form of geomorphology by visual method in deep-sea environment, a design scheme of line structured light 3D reconstruction vision sensor for deep-sea topography features based on Jiaolong manned submersible was presented. According to the principle of 3D reconstruction of linear structured light, firstly, the Steger algorithm was improved to extract the center line of laser fringes quickly and accurately, then direct calibration method was used to solve the 2D spatial coordinates of topographic features, and the influence of image distortion on reconstruction was overcame. Then, the obtained 2D point cloud was fused with multi-sensor data, and the offset was calculated in real time according to the coordinates of the submersible, and the image was corrected according to the change of sensor position and attitude. Finally, the 3D point cloud data of landform was obtained. According to the reconstruction principle, the hardware and software system of the vision sensor was designed, and an experimental simulation platform was built to verify the feasibility of the scheme. Through underwater experiments, the complete reconstruction of simulated geomorphology can be achieved, with an accuracy of 96.9%, which meets the reconstruction requirements.