The invention provides an underwater robot monocular vision positioning method for a complex environment, and belongs to the technical field of underwater image processing. Comprising the following steps: acquiring an underwater image through a monocular camera carried by an underwater robot, and performing distortion correction on the underwater image to obtain an underwater image after distortion correction; extracting a dense corresponding relation between two adjacent frames of images through an optical flow network, and filtering abnormal optical flow values based on a bidirectional consistency screening strategy; a scene depth map is predicted by using the deep network, and the optical flow network and the deep network are jointly trained by minimizing the target function mean value of each pixel in the whole image, so that underwater monocular vision positioning is realized. According to the underwater robot monocular vision autonomous positioning method, dependence on a large scale of underwater data sets containing labels is effectively avoided through a self-supervised learning mode, and the high-precision underwater robot monocular vision autonomous positioning method is achieved.
本发明提供一种面向复杂环境的水下机器人单目视觉定位方法,属于水下图像处理的技术领域。包括以下步骤:通过水下机器人搭载的单目相机获取水下图像,将所述水下图像进行畸变校正,得到畸变校正后的水下图像;通过光流网络提取相邻两帧图像之间的稠密对应关系,并基于双向一致性筛选策略过滤异常的光流值;利用深度网络预测出场景深度图,通过最小化整个图像中每个像素的目标函数均值来联合训练光流网络和深度网络,实现水下单目视觉定位。本发明通过自监督学习的方式有效避免对大规模含有标签的水下数据集的依赖,实现高精度的水下机器人单目视觉自主定位方法。
Underwater robot monocular vision positioning method for complex environment
一种面向复杂环境的水下机器人单目视觉定位方法
2025-05-30
Patent
Electronic Resource
Chinese
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