Viewpoint Optimization Using Genetic Algorithm for Flying Robot Inspection of Electricity Transmission Tower Equipment

YANG Guotian; DONG Ruifang; WU Hua; LIU Chang'an

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(2): 426-431

YANG Guotian, DONG Ruifang, WU Hua, et al., “Viewpoint Optimization Using Genetic Algorithm for Flying Robot Inspection of Electricity Transmission Tower Equipment,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 426-431, 2014,

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YANG Guotian, DONG Ruifang, WU Hua, et al., “Viewpoint Optimization Using Genetic Algorithm for Flying Robot Inspection of Electricity Transmission Tower Equipment,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 426-431, 2014,

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Viewpoint Optimization Using Genetic Algorithm for Flying Robot Inspection of Electricity Transmission Tower Equipment

School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61105083), Program for New Century Excellent Talents in University (No.NCET-11-0634), the Fundamental Research Funds for the Central Universities (No.11QG12, No.12ZX16), Beijing supports Joint Program for Central Universities in Beijing: "Research on the autonomous inspection method of robot for cable tunel".

More Information

Corresponding author: WU Hua
Received Date: 2012-12-01
Rev Recd Date: 2013-01-01
Publish Date: 2014-04-05

Abstract

Abstract

To fully exploit the limited flight-time of the flying robot, and ensure the successful visibility of target, viewpoint optimization is proposed in this paper for the inspection of electricity transmission tower equipment with an optimization function to determine the best viewpoints in a local viewpoint region. The local viewpoint regions are generated from the local objective regions which are determined by the geometrical structure of a priori 3D model for the electricity transmission tower equipment. The optimization function is structured based on three factors including visibility, viewing quality and observation distance. In addition, the fitness function of genetic algorithm is used to find the optimal viewpoint. The experimental results demonstrate the effectiveness and efficiency of the proposed viewpoint selection algorithm.
- Flying robot inspection,
- Electricity transmission tower equipment,
- Viewpoint optimization,
- Genetic algorithm,
- 3D model

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References(25)

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