基于混合算法的电力杆塔巡检实时航迹规划

doi:10.11930/j.issn.1004-9649.202003201

中国电力 ›› 2021, Vol. 54 ›› Issue (11): 214-220.DOI: 10.11930/j.issn.1004-9649.202003201

基于混合算法的电力杆塔巡检实时航迹规划

黄郑¹, 王红星¹, 周航², 张星炜¹, 赵宏伟²

1. 江苏方天电力技术有限公司,江苏南京 211102;
2. 南京航空航天大学民航学院,江苏南京 211106

收稿日期:2020-03-27 修回日期:2020-12-08 出版日期:2021-11-05 发布日期:2021-11-16
作者简介:黄郑(1990-),男,通信作者,工程师,从事输电线路无人机智慧巡检研究,E-mail:hz10@vip.qq.com;王红星(1974-),男,高级工程师(教授级),从事无人机智慧巡检相关技术研究,E-mail:whx@js.sgcc.com.cn
基金资助:
江苏方天电力技术有限公司科技项目(无人机智能巡检关键技术与三维平台应用，KJ201915)

Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm

HUANG Zheng¹, WANG Hongxing¹, ZHOU Hang², ZHANG Xingwei¹, ZHAO Hongwei²

1. Jiangsu Frontier Electric Technology Co., Ltd., Nanjing 211102, China;
2. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Received:2020-03-27 Revised:2020-12-08 Online:2021-11-05 Published:2021-11-16
Supported by:
This work is supported by Science and Technology Project of Jiangsu Frontier Electric Technology Co., Ltd. (No.KJ201915)

摘要/Abstract

摘要： 传统的电力杆塔拍摄视点顺序固定，多旋翼无人机巡检距离并非最优；同时，随着维度增加，航迹规划算法空间复杂度呈指数增长，不能满足实时规划航迹的需求。针对以上问题，提出一种基于蚁群和A*混合算法（ACO-A*）的电力杆塔巡检三维航迹规划方法。该方法分为全局规划和局部规划，全局规划利用改进蚁群算法找到覆盖所有视点的较优路径，并通过算法判断路径是否经过障碍物，再运用A*算法局部规划。仿真结果表明：ACO-A*算法规划的航迹长度比《架空输电线路无人机巡检影像拍摄指导手册》规定的巡检航迹降低了16.85%；ACO-A*算法路径规划时间比A*算法降低了99.68%。因此本方法既节约了巡检能耗，又提高了航迹规划的效率。

关键词: 三维航迹规划, 蚁群算法, A*算法, 混合算法, 电力杆塔巡检

Abstract: 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.

Key words: three-dimensional path planning, ant colony algorithm, A* algorithm, hybrid algorithm, power tower inspection

黄郑, 王红星, 周航, 张星炜, 赵宏伟. 基于混合算法的电力杆塔巡检实时航迹规划[J]. 中国电力, 2021, 54(11): 214-220.

HUANG Zheng, WANG Hongxing, ZHOU Hang, ZHANG Xingwei, ZHAO Hongwei. Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm[J]. Electric Power, 2021, 54(11): 214-220.

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https://www.electricpower.com.cn/CN/Y2021/V54/I11/214

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基于混合算法的电力杆塔巡检实时航迹规划

Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm

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