Generation and Visualization of Large-Scale Three-Dimensional Reconstructions from Underwater Robotic Surveys
Generation and Visualization of Large-Scale Three-Dimensional Reconstructions from Underwater Robotic Surveys
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DOI：
10.1002/rob.20324
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发表时间：
2010-01-01
影响因子：
8.3
通讯作者：
Mahon, Ian
中科院分区：
文献类型：
--
作者：
Johnson-Roberson, Matthew;Pizarro, Oscar;Mahon, Ian
鲁棒的、可扩展的同时定位和映射（SLAM）算法支持在现实世界应用中成功部署机器人。在许多情况下，这些平台从大规模的非结构化环境中提供大量的传感器数据。如果没有进一步的处理和合适的可视化工具，这些数据可能很难被最终用户解释。我们提出了一个强大的，自动化的系统，大规模的三维（3D）重建和可视化，需要立体图像从自主水下航行器（AUV）和基于SLAM的车辆构成提供详细的三维模型的海底纹理多边形网格的形式。我们的系统必须科普成千上万的图像，纹理化时产生视觉接缝的照明条件，以及校准，三角测量和导航错误引起的立体网格之间可能的不一致。我们的方法将问题分解为可管理的阶段，首先估计局部结构，然后结合这些估计，使用基于SLAM的车辆姿态估计来恢复复合地理参考结构。然后生成多个尺度的纹理映射表面，并通过可视化引擎交互式地呈现给用户。我们在可能的情况下调整现有的解决方案，重点是在标准计算硬件上快速提供近似但视觉上一致的重建。这使得科学家们能够在研究巡航中使用我们的系统来设计AUV和补充仪器的后续部署。到目前为止，该系统已经在澳大利亚沃茨的几次研究巡航中进行了测试，并已用于可靠地生成和可视化重建60多个潜水，覆盖不同的栖息地，并代表数百公里的线性调查。(C)2009 Wiley Periodicals，Inc.
Robust, scalable simultaneous localization and mapping (SLAM) algorithms support the successful deployment of robots in real-world applications. In many cases these platforms deliver vast amounts of sensor data from large-scale, unstructured environments. These data may be difficult to interpret by end users without further processing and Suitable visualization tools. We present a robust, automated system for large-scale three-dimensional (3D) reconstruction and visualization that takes stereo imagery from an autonomous underwater vehicle (AUV) and SLAM-based vehicle poses to deliver detailed 3D models of the seafloor in the form of textured polygonal meshes. Our system must cope with thousands of images, lighting conditions that create visual seams when texturing, and possible inconsistencies between stereo meshes arising from errors in calibration, triangulation, and navigation. Our approach breaks down the problem into manageable stages by first estimating local structure and then combining these estimates to recover a composite georeferenced structure using SLAM-based vehicle pose estimates. A texture-mapped surface at multiple scales is then generated that is interactively presented to the user through a Visualization engine. We adapt established solutions when possible, with an emphasis on quickly delivering approximate yet visually consistent reconstructions on standard computing hardware. This allows scientists oil a research cruise to use our system to design follow-up deployments of the AUV and complementary instruments. To date, this system has been tested on several research cruises in Australian waters and has been used to reliably generate and visualize reconstructions for more than 60 dives covering diverse habitats and representing hundreds of linear kilometers of survey. (C) 2009 Wiley Periodicals, Inc.