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PLineD: Vision-based power lines detection for Unmanned Aerial Vehicles

机译:PLineD:无人机的基于视觉的电力线检测

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It is commonly accepted that one of the most important factors for assuring the high performance of an electrical network is the surveillance and the respective preventive maintenance. From a long time ago that TSOs and DSOs incorporate in their maintenance plans the surveillance of the grid, where is included the aerial power lines inspection. Those inspections started by human patrol, including structure climbing when needed and later were substituted by helicopters with powerful sensors and specialised technicians. More recently the Unmanned Aerial Vehicles (UAV) technology has been used, taking advantage of its numerous advantages. This paper addresses the problem of improving the real-time perception capabilities of UAVs for endowing them with capabilities for safe and robust autonomous and semi-autonomous operations. It presents a new vision based power line detection algorithm denoted by PLineD, able to improve the detection robustness even in the presence of image with background noise. The algorithm is tested in real outdoor images of a dataset with multiple backgrounds and weather conditions. The experimental results demonstrate that the proposed approach is effective and able to implemented in real-time image processing pipeline.
机译:公认的是,确保电网高性能的最重要因素之一是监视和相应的预防性维护。长期以来,TSO和DSO在其维护计划中都包含了对电网的监视,其中包括空中电力线检查。这些检查是由人力巡逻开始的,包括在需要时进行结构攀爬,后来由配备强大传感器和专业技术人员的直升机代替。最近,利用无人飞行器(UAV)技术的众多优势。本文解决了提高无人机实时感知能力的问题,使无人机具有安全,强大的自主和半自主操作能力。它提出了一种新的基于视觉的电力线检测算法,以PLineD表示,即使在存在背景噪声的图像的情况下,也能够提高检测的鲁棒性。该算法在具有多个背景和天气条件的数据集的真实室外图像中进行了测试。实验结果表明,该方法是有效的,并且能够在实时图像处理流水线中实现。

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