Transmission Line Obstacle Detection Based on Structural Constraint and Feature Fusion

Author:

Ye XuhuiORCID,Wang Dong,Zhang Daode,Hu Xinyu

Abstract

Accurate detection and identification of obstacles plays an important role in the navigation and behavior planning of the patrol robot. Aiming at the patrol robot with camera mounted symmetrically, an obstacle detection method based on structural constraint and feature fusion is proposed. Firstly, in order to discover the region of interest, the bounding box algorithm is used to propose the region. The location of the detected ground wire is used to constrain the region, and the image block of interest is clipped. Secondly, in order to accurately represent the multi-view and multi-scale obstacle images, the global shape features and the improved local corner features are fused by different weights. Then, the particle swarm-optimized support vector machine (PSO-SVM) is used for classifying and recognizing obstacles. On block data set B containing multi-view and multi-scale obstacle images, the recognition rate of this method can reach up to 86.2%, which shows the effectiveness of weighted fusion of global and local features. On data set A containing complete images of different distances, the detection success rate of long-distance obstacles can reach 80.2%. The validity of the proposed method based on structural constraints and feature fusion is verified.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

MDPI AG

Subject

Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Detection of Foreign Objects Intrusion Into Transmission Lines Using Diverse Generation Model;IEEE Transactions on Power Delivery;2023-10

2. Obstacle Detection by Power Transmission Line Inspection Robot;Innovative Data Communication Technologies and Application;2022

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