A Vision-based Approach for Unmanned Aerial Vehicles to Track Industrial Pipes for Inspection Tasks

Abstract

Inspecting and maintaining industrial plants is an important and emerging field in robotics. A particular case is represented by the inspection of oil and gas refinery facilities consisting of different long pipe racks to be inspected repeatedly. This task is costly in terms of human safety and operation costs due to the high altitude location in which the pipes are placed. In this domain, we propose a visual inspection system for unmanned aerial vehicles (UAVs), allowing the autonomous tracking and navigation of the center line of the industrial pipe. The proposed approach exploits a depth sensor to generate the control data for the aerial platform and, at the same time, highlight possible pipe defects. A set of simulated and real experiments in a GPS-denied environment have been carried out to validate the visual inspection system.