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Robust obstacle detection for Unmanned Surface Vehicles

机译:无人水面车辆的鲁棒障碍物检测

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Obstacle detection is of essential importance for Unmanned Surface Vehicles (USV). Although some obstacles (e.g.. ships, islands) can be detected by Radar, there are many other obstacles (e.g., floating pieces of woods, swimmers) which are difficult to be detected via Radar because these obstacles have low radar cross section. Therefore, detecting obstacle from images taken onboard is an effective supplement. In this paper, a robust vision-based obstacle detection method for USVs is developed. The proposed method employs the monocular image sequence captured by the camera on the USVs and detects obstacles on the sea surface from the image sequence. The experiment results show that the proposed scheme is efficient to fulfill the obstacle detection task.
机译:障碍物检测对于无人水面飞行器(USV)至关重要。尽管雷达可以检测到某些障碍物(例如,船舶,岛屿),但由于这些障碍物的雷达横截面较低,因此难以通过雷达检测​​到许多其他障碍物(例如,漂浮的树林,游泳者)。因此,从船上拍摄的图像中检测障碍物是有效的补充。在本文中,开发了一种鲁棒的基于视觉的无人飞行器障碍物检测方法。所提出的方法利用由照相机在USV上捕获的单眼图像序列,并从图像序列中检测出海面上的障碍物。实验结果表明,该方案能够有效地完成障碍物检测任务。

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