Abstract
This article presents an autonomous navigation approach based on a transmission tower for unmanned aerial vehicle (UAV) power line inspection. For this complex vision task, a perspective navigation model, which plays an important role in the description and analysis of the flight strategy, is introduced. Based on the proposed navigation model, valuable cues are excavated from a perspective image, which enhances the capability of the perception of three-dimensional direction and simultaneously improves the safety of intelligent inspection. Specifically, for robust and continuous localization of the transmission tower, a developed detecting-tracking visual strategy—comprised tower detection based on a faster region-based convolutional neural network and tower tracking by kernelized correlation filters—is presented. Further, segmentation by fully convolutional networks is applied to the extraction of transmission lines, from which the vanishing point (VP), an important basis for determining the flight heading, can be obtained. For more robust navigation, the designed scheme addresses the scenario of a nonexistent VP. Finally, the proposed navigation approach and constructed UAV platform were evaluated in a practical environment and achieved satisfactory results. To the best of our knowledge, this article marks the first time that a navigation approach based on a transmission tower is proposed and implemented.
Highlights
High-voltage transmission lines are vital to economic development; they lack regular maintenance
Many intelligent inspection studies have been conducted on two major platforms, the unmanned aerial vehicle (UAV) and crawling robot.[1,2,3]
We focus on the problem of autonomous navigation based on the transmission tower, which enables power infrastructure inspection
Summary
High-voltage transmission lines are vital to economic development; they lack regular maintenance. The inefficiency of existing inspection and maintenance methods leads to a considerable amount of wasted resources. With the rapidly expanded scale of overhead transmission lines, intelligent inspection has received an increasing amount of attention. Many intelligent inspection studies have been conducted on two major platforms, the unmanned aerial vehicle (UAV) and crawling robot.[1,2,3] Compared with crawling robots, UAVs provide greater flexibility, a broader operation range, and higher speed. Autonomous navigation, an important component of intelligent inspection, has been relying on accurate global positioning system (GPS) or reliable recognition of transmission lines. For GPS-based autonomous navigation systems, ground stations and real-time and accurate GPS data
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