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自主水下机器人:图像采集的关键问题与未来展望

Autonomous Underwater Vehicles: Identifying Critical Issues and Future Perspectives in Image Acquisition.

机构信息

Department of Applied Mathematics I, Universidad de Sevilla, 41012 Sevilla, Spain.

Department of Computer Architecture and Technology, Universidad de Sevilla, 41012 Sevilla, Spain.

出版信息

Sensors (Basel). 2023 May 22;23(10):4986. doi: 10.3390/s23104986.

Abstract

Underwater imaging has been present for many decades due to its relevance in vision and navigation systems. In recent years, advances in robotics have led to the availability of autonomous or unmanned underwater vehicles (AUVs, UUVs). Despite the rapid development of new studies and promising algorithms in this field, there is currently a lack of research toward standardized, general-approach proposals. This issue has been stated in the literature as a limiting factor to be addressed in the future. The key starting point of this work is to identify a synergistic effect between professional photography and scientific fields by analyzing image acquisition issues. Subsequently, we discuss underwater image enhancement and quality assessment, image mosaicking and algorithmic concerns as the last processing step. In this line, statistics about 120 AUV articles fro recent decades have been analyzed, with a special focus on state-of-the-art papers from recent years. Therefore, the aim of this paper is to identify critical issues in autonomous underwater vehicles encompassing the entire process, starting from optical issues in image sensing and ending with some issues related to algorithmic processing. In addition, a global underwater workflow is proposed, extracting future requirements, outcome effects and new perspectives in this context.

摘要

水下成像是一个存在了几十年的领域,因为它与视觉和导航系统有关。近年来,机器人技术的进步使得自主或无人水下航行器(AUV、UUV)成为可能。尽管该领域的新研究和有前途的算法发展迅速,但目前缺乏标准化的通用方法的研究。这一问题在文献中被认为是未来需要解决的一个限制因素。这项工作的关键起点是通过分析图像采集问题,发现专业摄影和科学领域之间的协同作用。随后,我们讨论了水下图像增强和质量评估、图像拼接和算法问题作为最后处理步骤。在此基础上,分析了近几十年来 120 篇关于 AUV 的文章,特别关注近年来的最新论文。因此,本文的目的是识别自主水下航行器中从图像传感中的光学问题到与算法处理相关的一些问题的整个过程中的关键问题。此外,还提出了一个全局水下工作流程,提取了这方面的未来需求、结果影响和新视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42b3/10222422/b9066f395b57/sensors-23-04986-g001.jpg

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