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Automatic Docking Based on Visual Feedback on Remotely Operated Vehicle

机译:基于视觉反馈的遥控车辆自动对接

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Corals are defenders of destructive waves, home for fishes, and also a tourist attraction. In a past few years, corals lost their colors due to global warming. The development of robotics makes it possible to aid coral rehabilitation utilizing ROV (Remotely Operated Vehicle). This paper presents an automatic docking method for ROV using a camera as feedback. A marker is placed under a docking station. ROV estimates its position and orientation relative to this marker. PID control is then used to maintain its position and orientation to the marker. The system is applied on Raspberry Pi 3. The marker detection algorithm takes 0.2 s in each iteration on this platform. The rise time of position control is 20 s and 25 s for orientation control. ROV approaches the marker at 0.66 cm/s in a calm water condition. The docking system is proven to be accurate with 4.7% of position error and 11% of orientation error. The algorithm is proven to be applicable on a small computer such as Raspberry Pi.
机译:珊瑚是毁灭性海浪的捍卫者,鱼类的家园,也是一个旅游胜地。在过去的几年中,由于全球变暖,珊瑚失去了颜色。机器人技术的发展使得利用ROV(遥控车)协助珊瑚康复成为可能。本文提出了一种使用摄像机作为反馈的ROV自动对接方法。将标记放置在扩展坞下方。 ROV估计其相对于此标记的位置和方向。然后使用PID控制来保持其相对于标记的位置和方向。该系统在Raspberry Pi 3上应用。标记检测算法在该平台上的每次迭代花费0.2 s。位置控制的上升时间为20 s和25 s。在平静的水条件下,ROV以0.66 cm / s的速度接近标记。事实证明,对接系统具有4.7%的位置误差和11%的方向误差,因此是准确的。实践证明,该算法可在Raspberry Pi等小型计算机上使用。

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