This work proposes a novel drone system designed to autonomously track and follow power lines and reconstruct them in 3D with a point cloud representation based on mmWave radar measurements. The system is composed of a GNSS-enabled quadrotor UAV equipped with a combined mmWave radar sensor and onboard compute module payload and has been designed to be small, lightweight, and low-cost.
MmWave radar sensors offer great range and sensitivity in the task of power line detection with a high level of sparsity in the produced data when compared to traditional sensors such as LiDARs. The proposed system overcomes the radar sensor's shortcomings by building up a point cloud representing the power line environment as the drone moves around in it. The built-up point cloud is analyzed using the onboard computer to detect the cables in the power line environment and to produce pose-estimates of each line.
The system has been tested in a variety of scenarios and has been shown to be able to accurately detect and track power lines in varying weather conditions.
@article{malle2024radar,
title = "Autonomous Power Line Tracking using mmWave Radar",
author = "Malle, {Nicolaj Haarh{\o}j} and Emad Ebeid",
booktitle = "2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)",
year = "2024",
organization = {IEEE}
}
