Drone Infrastructure Inspection and Interaction

 

 


Autonomous Power Line Tracking using mmWave Radar

 

Nicolaj Malle and Emad Ebeid


 

 


Introduction

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.

 


Code, setup, and paper

Code

Setup

Paper

 


Video demonstrations

 


BibTeX Citation

@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} }