Autonomous Power Line Tracking with mmWave Radar

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.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802812
Citations
2
Primary Topic
Vehicle License Plate Recognition
Type
article
Field-Weighted Citation Impact
0.64

Funders

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article

Autonomous Power Line Tracking with mmWave Radar

Nicolaj Haarhøj Malle, Emad Ebeid
2 citations
Vehicle License Plate Recognition
0.64
article

Autonomous Power Line Tracking with mmWave Radar

Nicolaj Haarhøj Malle, Emad Ebeid
article en
2 citations

Abstract

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.

University of Southern Denmark (DK)
European Commission
Affordable and clean energy
Openalex Percentile: Top 25%
Vehicle License Plate Recognition
0.64
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Autonomous Power Line Tracking with mmWave Radar — Nicolaj Haarhøj Malle, Emad Ebeid · (2024) | TGRS Research Map | TGRS