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Concept of an autonomous mobile robotic system for bridge inspection

机译:桥梁检查自主移动机器人系统的概念

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In the next decade, many old bridges will be exposed to increasing traffic loads and destructive environmental conditions. Measurement methods like laser scanning, infrared thermography, photogrammetry, ground penetrating radar, or ultrasonic scanning are used on single robotic systems to partially support the inspectors. However, time-consuming manual inspections for crack detection, measurement, and documentation are still necessary. This paper describes the concept of an autonomous mobile robotic bridge inspection system. The proposed concept for an unmanned ground vehicle (UGV) is achieved by a trade-off of different mobile platforms, sensor systems for mapping, localization and inspection, and first tests assessing the feasibility. We use a small concrete bridge in Freiburg (Germany) with various cracks for testing the sensors, the UGV concept, and initial tests of the mobile platform. This results in the choice of selecting the weatherproof version of the mobile robotic platform Husky from Clearpath Robotics. It is equipped with Swift Navigation's Duro real-time kinematic (RTK) system, a heading system, an inertial measurement unit (IMU), a base station, and software for semi-autonomous navigation. In the next step, we compare different sensor systems. For mapping and localization, we decide to use the 360° spherical camera Ladybug 5+ from FLIR Systems and a Velodyne VLP-16 light detection and ranging (LiDAR). High-resolution cameras allow recording damages on the bridge's surface. We perform first tests using monochrome and colour cameras. After evaluating different sensor integration concepts, we present a preliminary design of the UGV including integrated sensors.
机译:在未来十年中,许多旧桥梁将接触到增加交通负荷和破坏性环境条件。在单个机器人系统上使用了激光扫描,红外热成像,摄影测量,地面穿透雷达或超声波扫描等测量方法,以部分地支持检查器。但是,仍然需要耗时的裂缝检测,测量和文档的手动检查。本文介绍了自主移动机器人桥检查系统的概念。通过不同移动平台的权衡,用于映射,定位和检查的传感器系统,以及评估可行性的首次测试来实现无人机地面车辆(UGV)的拟议概念。我们在弗赖堡(德国)中使用一个小型混凝土桥,具有各种裂缝,用于测试传感器,UGV概念和移动平台的初始测试。这导致选择从ClearPath机器人中选择移动机器人平台哈士奇的防风雨版本。它配备了SWIFT导航的DURO实时运动(RTK)系统,标题系统,惯性测量单元(IMU),基站和用于半自动导航的软件。在下一步中,我们比较不同的传感器系统。为了映射和本地化,我们决定使用来自FLIR系统的360°球形摄像头瓢虫5+,并Velodyne VLP-16光检测和测距(LIDAR)。高分辨率摄像头允许在桥梁表面上记录损坏。我们使用单色和彩色相机执行第一次测试。在评估不同的传感器集成概念之后,我们提出了UGV的初步设计,包括集成传感器。

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