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Powerline Detection and Accurate Localization Method Based on the Depth Image

  • Hai Li
  • , Zhan Li*
  • , Tong Wu
  • , Fulin Song
  • , Jiayu Liu
  • , Zonglin Li
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Peng Cheng Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, various types of aerial work robots have been developed for the inspection and maintenance of the powerline. In this regard, the aerial manipulator system (AMS) has shown broad application potential because it combines the advantages of the UAVs and the manipulator. However, it is full of challenges for the AMS to perform close-range aerial interactive operations on the powerline, which requires stable and accurate detection and positioning information of the powerline. Therefore, a powerline detection and accurate localization method based on the depth image is proposed. Firstly, the depth image is converted into a grayscale image through background filtering and a designed special mapping operator. Then, detect the edges of the powerline in the grayscale image and identify different powerlines. Finally, the Kalman filter is used to track the position of the powerline and obtain the accurate localization information. The experimental results show that the proposed method can stably detect and accurately locate the powerline, which can provide stable and reliable relative position information for close-range aerial interactive operations.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings
EditorsHuayong Yang, Jun Zou, Geng Yang, Xiaoping Ouyang, Honghai Liu, Zhouping Yin, Lianqing Liu, Zhiyong Wang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages317-328
Number of pages12
ISBN (Print)9789819965007
DOIs
StatePublished - 2023
Event16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 - Hangzhou, China
Duration: 5 Jul 20237 Jul 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14274 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Intelligent Robotics and Applications, ICIRA 2023
Country/TerritoryChina
CityHangzhou
Period5/07/237/07/23

Keywords

  • Accurate localization
  • Depth image
  • Kalman filter
  • Powerline detection

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