Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm
The sequence of conventional shooting viewpoints for power tower is fixed and the inspection distance of multi-rotor UAV is not optimal. In addition, as the dimension increases, the path planning algorithm cannot meet the requirements of real-time path planning because the space complexity increases...
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| Format: | Article |
| Language: | zho |
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State Grid Energy Research Institute
2021-11-01
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| Series: | Zhongguo dianli |
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| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202003201 |
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| author | Zheng HUANG Hongxing WANG Hang ZHOU Xingwei ZHANG Hongwei ZHAO |
| author_facet | Zheng HUANG Hongxing WANG Hang ZHOU Xingwei ZHANG Hongwei ZHAO |
| author_sort | Zheng HUANG |
| collection | DOAJ |
| description | The sequence of conventional shooting viewpoints for power tower is fixed and the inspection distance of multi-rotor UAV is not optimal. In addition, as the dimension increases, the path planning algorithm cannot meet the requirements of real-time path planning because the space complexity increases exponentially. Aiming at those problems, a three-dimensional path planning method for power tower inspection is proposed based on ant colony optimization and A * (ACO-A*) hybrid algorithm. The method is composed of global planning and local planning. Firstly, the global planning uses the ant colony optimization algorithm to find a relatively optimal path that covers all viewpoints, and to judge whether the path passes through obstacles. And then the A* algorithm is used for local planning. The simulation results show that the path length planned by the proposed ACO-A* algorithm is reduced by 16.68% compared to that stipulated in the Shooting Manual for UAV Inspection Images of Overhead Transmission Lines, and the path planning time is reduced by 99.68% compared to that of the A* algorithm. Therefore, the proposed method not only reduces the energy consumption for inspection, but also enhances the efficiency of path planning. |
| format | Article |
| id | doaj-art-15a99ad9c2ef4151b4d879de0280cf24 |
| institution | DOAJ |
| issn | 1004-9649 |
| language | zho |
| publishDate | 2021-11-01 |
| publisher | State Grid Energy Research Institute |
| record_format | Article |
| series | Zhongguo dianli |
| spelling | doaj-art-15a99ad9c2ef4151b4d879de0280cf242025-08-20T02:59:18ZzhoState Grid Energy Research InstituteZhongguo dianli1004-96492021-11-01541121422010.11930/j.issn.1004-9649.202003201zgdl-53-8-huangzhengReal-Time Path Planning for Power Tower Inspection Based on Hybrid AlgorithmZheng HUANG0Hongxing WANG1Hang ZHOU2Xingwei ZHANG3Hongwei ZHAO4Jiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, ChinaJiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaJiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThe sequence of conventional shooting viewpoints for power tower is fixed and the inspection distance of multi-rotor UAV is not optimal. In addition, as the dimension increases, the path planning algorithm cannot meet the requirements of real-time path planning because the space complexity increases exponentially. Aiming at those problems, a three-dimensional path planning method for power tower inspection is proposed based on ant colony optimization and A * (ACO-A*) hybrid algorithm. The method is composed of global planning and local planning. Firstly, the global planning uses the ant colony optimization algorithm to find a relatively optimal path that covers all viewpoints, and to judge whether the path passes through obstacles. And then the A* algorithm is used for local planning. The simulation results show that the path length planned by the proposed ACO-A* algorithm is reduced by 16.68% compared to that stipulated in the Shooting Manual for UAV Inspection Images of Overhead Transmission Lines, and the path planning time is reduced by 99.68% compared to that of the A* algorithm. Therefore, the proposed method not only reduces the energy consumption for inspection, but also enhances the efficiency of path planning.https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202003201three-dimensional path planningant colony algorithma* algorithmhybrid algorithmpower tower inspection |
| spellingShingle | Zheng HUANG Hongxing WANG Hang ZHOU Xingwei ZHANG Hongwei ZHAO Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm Zhongguo dianli three-dimensional path planning ant colony algorithm a* algorithm hybrid algorithm power tower inspection |
| title | Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm |
| title_full | Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm |
| title_fullStr | Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm |
| title_full_unstemmed | Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm |
| title_short | Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm |
| title_sort | real time path planning for power tower inspection based on hybrid algorithm |
| topic | three-dimensional path planning ant colony algorithm a* algorithm hybrid algorithm power tower inspection |
| url | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202003201 |
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