Sonar Visual Inertial SLAM of Underwater Structures
Sonar Visual Inertial SLAM of Underwater Structures
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DOI：
10.1109/icra.2018.8460545
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
S. Rahman;Alberto Quattrini Li;Ioannis M. Rekleitis
中科院分区：
文献类型：
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作者：
S. Rahman;Alberto Quattrini Li;Ioannis M. Rekleitis
本文提出了一种扩展的最先进的视觉惯性状态估计包（OKVIS），以适应数据从水声传感器。绘制水下结构图在海洋考古学、搜索和救援、资源管理、水文地质学和洞穴学等多个领域都很重要。然而，收集数据是一项具有挑战性的、危险的和令人精疲力竭的任务。水下领域对可用视觉数据的质量提出了独特的挑战;因此，使用声学范围数据增强外感受性传感可以改善水下结构的重建。水下沉船，水下洞穴，和一个淹没的巴士的实验结果证明了我们的方法的性能。
This paper presents an extension to a state of the art Visual-Inertial state estimation package (OKVIS) in order to accommodate data from an underwater acoustic sensor. Mapping underwater structures is important in several fields, such as marine archaeology, search and rescue, resource management, hydrogeology, and speleology. Collecting the data, however, is a challenging, dangerous, and exhausting task. The underwater domain presents unique challenges in the quality of the visual data available; as such, augmenting the exteroceptive sensing with acoustic range data results in improved reconstructions of the underwater structures. Experimental results from underwater wrecks, an underwater cave, and a submerged bus demonstrate the performance of our approach.