UAV transmission line transfer-acceptance technology based on vision

Sijiang Zhang; Zhengfa Li; Linke Huang; Kangwei Jia; Dongsheng Zhang

doi:10.1117/12.3014392

9 January 2024 UAV transmission line transfer-acceptance technology based on vision

Sijiang Zhang, Zhengfa Li, Linke Huang, Kangwei Jia, Dongsheng Zhang

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129692S (2024) https://doi.org/10.1117/12.3014392
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

To address the challenges of manual transmission line inspection and UAV line-following flights, this study presents a systematic UAV line tracking method based on binocular vision. The proposed method involves several key steps. First, the camera captures images of the transmission lines during flight, and these visual inputs are continually updated in realtime. Second, the images undergo pre-processing using Gaussian blur and bilateral filtering algorithms to mitigate the impact of light and noise interference on image detection. Subsequently, the 3D nodes of the line within the image are detected and extracted using the Hough transform and BM algorithm. The 3D pose of the specified tracking line is then determined using the least squares algorithm. Lastly, a visual guidance strategy is presented for the UAV to effectively track the designated line. The real-time capability and accuracy of the method are validated through experimental verification.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Sijiang Zhang, Zhengfa Li, Linke Huang, Kangwei Jia, and Dongsheng Zhang "UAV transmission line transfer-acceptance technology based on vision", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129692S (9 January 2024); https://doi.org/10.1117/12.3014392

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available