Drone Path Planning and Object Detection via QR Codes; A Surrogate Case Study for Wind Turbine Inspection
Branden Pinney, Shayne Duncan, Mohammad Shekaramiz, Mohammad A. S. Masoum
Abstract
This case study shows the initial results of aiming for reducing the cost, man-hours, and safety risks involved with the external structural inspection process of wind turbines using a fully automated drone-based system. The end goal is to use object detection and path planning algorithms to automate the process of identifying a specific wind turbine in the field via a drone, safely approaching the wind turbine, and capturing the images necessary for analysis and inspection. Our case study here serves as a small-scale proof of concept for the path planning solutions using pedestal fans in the place of wind turbines and a Tello EDU drone. Our study demonstrates the success of the drone to autonomously explore the region of interest, detect the desired fan, safely approach the fan, verify the fan via scanning the associated QR code, capture video and images from multiple angles, and safely fly back to the starting point and land.