NRI: Enhancing Mapping Capabilities of Underwater Caves using Robotic Assistive Technology

该项目开发机器人辅助技术，以提高水下洞穴的测绘能力。该项目能够实际构建充满水的洞穴的精确体积模型。这种机器人系统的技术也可以部署在水下航行器上，从而能够自主探索洞穴和其他水下结构。所开发的技术也可用于空中和地面车辆的某些应用中。从开发的传感器现场部署收集的数据通过公共领域发布提供给更广泛的机器人，地质和洞穴学研究社区，以进一步创新。此外，在开源许可下发布的数据和软件使研究人员能够在具有挑战性的环境中测试计算机视觉，状态估计和传感器融合算法。该项目通过培训研究生和本科生以及加强南卡罗来纳州大学的几门研究生和本科生课程，将研究和教育结合起来。该项目还吸引了本尼迪克特学院的本科生，这是一所历史上的黑人学院或大学（HBCU）。收集到的数据被用于外展活动，以招募大哥伦比亚地区的高中生进行STEM教育，吸引学生和教育工作者，特别是在服务不足的社区。这项研究开发了利用洞穴系统的环境特性的3D重建算法。该研究团队研究了用于在单个单元中融合多个数据流的传感器的机器人技术，并通过与专家洞穴潜水员合作进行水下洞穴探索的广泛测试，对开发的系统进行了实验验证。该项目通过利用现有做法分三个步骤将机器人技术引入水下洞穴探险界：（a）部署立体摄像机，与潜水员携带的结构光一起使用;（B）开发一个纯方位合作定位系统，用于准确记录已探险洞穴的骨架;（c）开发一套传感器，将惯性测量装置、声纳、深度和视觉数据与状态估计算法无缝结合，用于洞穴体积测绘。该项目通过以下方式提高了水下洞穴测绘能力：1）测绘区域的规模，2）通过减少潜水员在勘探期间的认知负荷来提高他们的安全性，3）制作地图的质量。

This project develops robotic assistive technologies to improve mapping capabilities of underwater caves. The project enables the practical construction of accurate volumetric models for water-filled caves. The technology of this robotic system can also be deployed on underwater vehicles enabling the autonomous exploration of caves and other underwater structures. The developed techniques can also be used in some applications of aerial and ground vehicles. Collected data from field deployments of the developed sensor are made available to the wider robotic, geological, and speleological research community through public-domain releases in order to further innovation. Furthermore, the data and software, released under an open-source license, enable researchers to test algorithms on computer vision, state estimation, and sensor fusion, in challenging environments. The project integrates research and education through training graduate and undergraduate students and enhancing several graduate and undergraduate courses at the University of South Carolina. The project also engages undergraduate students from Benedict College, a Historically Black College or University (HBCU). The collected data are used in outreach activities to recruit high-school students of the greater Columbia area in STEM education, engaging students and educators, particularly in underserved communities.This research develops 3D reconstruction algorithms utilizing the environmental characteristic of a cave system. The research team studies robotic technologies for sensor fusion of multiple data streams in a single unit and validates experimentally the developed system via extensive testing in underwater cave explorations in collaboration with expert cave divers. The project introduces robotic technology to the underwater cave explorer community by capitalizing on existing practices in three steps: (a) deploying stereo cameras to be used in conjunction with structured light carried by the divers, (b) developing a bearing-only Cooperative Localization system for accurately recording the skeleton of explored caves; (c) developing a sensor suite that seamlessly integrates inertial measurement unit, sonar, depth, and visual data with state estimation algorithms for the volumetric mapping of the cave. The project enhances underwater cave mapping abilities by increasing: 1) the scale of the area mapped, 2) the safety of the divers by reducing their cognitive load during exploration and 3) the quality of the produced maps.