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Savannah River Site H-Canyon Tunnel Inspection LiDAR Mapping Solution - 19477

机译:萨凡纳河网站H峡谷隧道检测LIDAR测绘解决方案 - 19477年

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Over the summer of 2018, the Savannah River National Laboratory (SRNL) formed and hosted a robotics and sensor intern team and tasked them with developing a proof of concept for a modular sensor suite to be deployed in the next H-Canyon Air Exhaust (HCAEX) Tunnel inspection in spring 2019. The developed sensor suite includes a planar LiDAR sensor for depth imaging, two Panospheric 4K cameras, and an inertial measurement unit to aid in base localization. The LiDAR is actuated to rotate about the vertical axis, which allows for the team to gather 3D mapping data. These rotating planar scans can also be fused with the camera and IMU data to generate colorized internal maps of the tunnel. The supporting software was developed iteratively over the summer and leveraged prior research conducted at the University of Texas at Austin, which facilitated the stitching of LiDAR scans, the fusion of the sensor data, and even algorithms to provide in-situ navigation feedback to the operators of the crawler. This software simultaneously represents huge leaps forward in the mapping and degradation measurement abilities of the crawler over past inspection units, while also allowing the operator much greater situational awareness. The improvement in awareness reduces risks of the robot becoming stuck or disabled inside the tunnel, which would jeopardize the success of both this and future inspections.
机译:在2018年夏天,大草原河国家实验室(SRNL)成立并举办了一个机器人和传感器实习生,并考虑了他们开发一个模块化传感器套件的概念证明,以便在下一个H-Canyon排气排气(HCAEX )2019年春季隧道检查。开发的传感器套件包括用于深度成像,两个Panosheric 4K摄像机和惯性测量单元的平面激光雷达传感器,以帮助基础定位。 LIDAR被致动以绕垂直轴旋转,这允许团队收集3D映射数据。这些旋转平面扫描也可以与相机和IMU数据融合以生成隧道的彩色内部地图。支持软件在夏季开发迭代开发,并在奥斯汀的德克萨斯大学进行的先前研究,这促进了激光扫描的缝合,传感器数据的融合,甚至算法为运营商提供了原位导航反馈爬行者。该软件同时代表了在过去的检查单元上爬行的映射和降级测量能力的巨大跨利赛,同时还允许操作员更大的情境感知。意识的提高减少了机器人在隧道内陷入困境或禁用的机器人的风险,这将危及这两个和未来检查的成功。

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