Vision-Based Monitoring of Locally Linear Structures Using an Unmanned Aerial Vehicle

Abstract

Inspecting and monitoring oil-gas pipelines, roads, rivers, and canals are very important in ensuring the reliability and life expectancy of these civil systems. An autonomous unmanned aerial vehicle (UAV) can decrease the operational costs, expedite the monitoring process, and be used in situations where a manned inspection is not possible. This paper addresses the problem of monitoring these systems using an autonomous UAV based on visual feedback. A single structure detection algorithm that can identify and localize various structures including highways, roads, and canals is presented in the paper. A fast learning algorithm that requires minimal supervision is applied to obtain detection parameters. The real time detection algorithm runs at 5 Hz or more with the onboard video collected by the UAV. Both hardware simulations and flight results of the vision-based control algorithm are presented in this paper. A fixed wing UAV equipped with a camera onboard was able to track a 700 m canal based on vision several times with an average cross-track error of around 10 m.