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Development of Object Tracking System Using Remotely Operated Vehicle Based on Visual sensor

机译:基于视觉传感器的遥控车辆目标跟踪系统的开发

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The use of the camera on ROV aims to visualize the ROV work environment so as to facilitate the operator on the surface to control the movement of ROV. In an attempt to track an object, it is too difficult for the operator to maintain object position that remains in point of view camera. The number of disturbances such as water currents can cause the object to disappear from point of view camera. For that reason, we developed an object tracking system on ROV (Remotely Operated Vehicle) that can approach object autonomously by utilizing camera as a visual sensor. The camera on the ROV is utilized as a visual sensor that sends feedback in the actual position of the ROV to determine the direction movement against the object. Tracking method is applied by utilizing the color as a feature because this method is very good in detecting objects with stable lighting. Real-time captured images will be processed with image processing to obtain a relative estimate of the object position. The estimate value of the object position is sent to the controller to move the ROV according to the direction and position of the object. Autonomous object tracking system on the ROV is divided into several stages; the first stage is image processing to detect the shape and the actual position of the object. The next stage is to connect the whole system. The performance of the developed system during the experiment takes about 20 seconds to reach ideal position. The image generated by image processing will be described in this paper.
机译:在ROV上使用摄像机的目的是可视化ROV的工作环境,以便于操作员在地面上控制ROV的移动。在试图跟踪物体时,操作者很难保持观察相机中保持的物体位置。诸如水流之类的干扰因素会导致物体从摄像机的角度消失。因此,我们开发了基于ROV(遥控车辆)的对象跟踪系统,该系统可以通过使用摄像头作为视觉传感器来自动接近对象。 ROV上的摄像头用作视觉传感器,可在ROV的实际位置中发送反馈,以确定相对于对象的方向运动。通过利用颜色作为特征来应用跟踪方法,因为该方法在检测具有稳定照明的物体方面非常好。实时捕获的图像将通过图像处理进行处理,以获取物体位置的相对估计值。物体位置的估计值被发送到控制器以根据物体的方向和位置移动ROV。 ROV上的自主对象跟踪系统分为几个阶段;第一阶段是图像处理,以检测物体的形状和实际位置。下一步是连接整个系统。实验过程中开发系统的性能大约需要20秒才能达到理想位置。本文将介绍通过图像处理生成的图像。

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