面向飞机表面视觉检查的无人机覆盖路径规划

doi:10.12305/j.issn.1001-506X.2025.04.17

Abstract

Abstract:

In order to efficiently plan the flight paths for unmanned aerial vehicle (UAV) conducting visual inspection tasks on aircraft surface, a coverage path planning algorithm is proposed by using an adaptive hybrid sampling strategy, which involves viewpoint generation, viewpoint selection, and coverage path planning to determine the optimal inspection path for UAV. Firstly, optimal line-of-sight sampling and adaptive supplementary sampling are performed based on the aircraft model to be inspected to generate a redundant set of viewpoints. Secondly, a heuristic graph search algorithm based on dynamic weighting is adopted to search and select a set of effective viewpoints to offer incremental coverage. Finally, a path collision detection module is designed in the original Lin-Kernighan heuristic (LKH) algorithm and the improved LKH algorithm is used to solve UAV collisionless inspection path.Simulation experimental results demonstrate that the proposed method achieves max aircraft surface coverage rates of 93.44% and 96.44% of the aircraft inspection paths planned in two different scenarios, which outperforms other comparative algorithms in terms of path length, number of viewpoints, and algorithmic time consumption.

Key words: aircraft surface inspection, coverage path planning, adaptive hybrid sampling, graph search algorithm, unmanned aerial vehicle (UAV)

CLC Number:

Wei CHEN, Congqing WANG, Qiang ZENG, Zhan LI. UAV coverage path planning for aircraft surface visual inspection[J]. Systems Engineering and Electronics, 2025, 47(4): 1206-1213.

Figures/Tables 12

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References 30

1	TSUZUKI R . Development of automation and artifici al intelligence technology for welding and inspection process in aircraft industry[J]. Welding in the World, 2022, 66 (1): 105- 116. doi: 10.1007/s40194-021-01210-3
2	KATUNIN A , DRAGAN K . Qualitative to quantitative non-destructive evaluation: a concept for D-sight inspections of aircraft structures[J]. Applied Mechanics and Materials, 2022, 909, 69- 74. doi: 10.4028/p-d8r1x7
3	MENG D , BOER W U , JUAN X U , et al. Visual inspection of aircraft skin: automated pixel-level defect detection by instance segmentation[J]. Chinese Journal of Aeronautics, 2022, 35 (10): 254- 264. doi: 10.1016/j.cja.2022.05.002
4	XU Y P, TANG J J, ZHOU J, et al. Intelligent itinerant inspection technology of aircraft based on deep learning and AR[C]//Proc. of the 5th World Conference on Mechanical Engineering and Intelligent Manufacturing, 2022: 1023-1027.
5	LIU Y P , DONG J X , LI Y D , et al. A UAV-based aircraft surface de fect inspection system via external constraints and deep learning[J]. IEEE Trans.on Instrumentation and Measurement, 2022, 71, 1- 15.
6	DEANE S , AVDELIDIS N P , IBARRA-CASTANEDO C , et al. Development of a thermal excitation source used in an active thermographic UAV platform[J]. Quantitative Infrared Thermography Journal, 2023, 20 (4): 198- 229. doi: 10.1080/17686733.2022.2056987
7	SAHA A, KUMAR L, SORTEE S, et al. An autonomous aircraft inspection system using collaborative unmanned aerial vehicles[C]//Proc. of the IEEE Aerospace Conference, 2023.
8	FEVGAS G , LAGKAS T , ARGYRIOU V , et al. Coverage path planning methods focusing on energy efficient and cooperative strategies for unmanned aerial vehicles[J]. Sensors, 2022, 22 (3): 1235. doi: 10.3390/s22031235
9	CAO Y , CHENG X H , MU J Z . Concentrated coverage path planning algorithm of UAV formation for aerial photography[J]. IEEE Sensors Journal, 2022, 22 (11): 11098- 11111. doi: 10.1109/JSEN.2022.3168840
10	KYRIAKAKIS N A , MARINAKI M , MATSATSINIS N , et al. A cumulative unmanned aerial vehicle routing problem approach for humanitarian coverage path planning[J]. European Journal of Operational Research, 2022, 300 (3): 992- 1004. doi: 10.1016/j.ejor.2021.09.008
11	SHI Y , ZHANG Y Y . The neural network methods for solving traveling salesman problem[J]. Procedia Computer Science, 2022, 199, 681- 686. doi: 10.1016/j.procs.2022.01.084
12	GIORDAN D , ADAMS M S , AICARDI I , et al. The use of unmanned aerial vehicles (UAVs) for engineering geology applications[J]. Bulletin of Engineering Geology and the Environment, 2020, 79, 3437- 3481. doi: 10.1007/s10064-020-01766-2
13	JING W, POLDEN J, LIN W, et al. Sampling-based view planning for 3D visual coverage task with unmanned aerial vehi cle[C]//Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016: 1808-1815.
14	BIRCHER A, ALEXIS K, BURRI M, et al. Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics[C]//Proc. of the IEEE International Conference on Robotics and Automation, 2015: 6423-6430.
15	ABDI A , RANJBAR M H , PARK J H . Computer vision-based path planning for robot arms in three-dimensional workspaces using Q-learning and neural networks[J]. Sensors, 2022, 22 (5): 1697. doi: 10.3390/s22051697
16	ALEXIS K, PAPACHRISTOS C, SIEGWART R, et al. Uniform coverage structural inspection path-planning for micro aerial vehicles[C]//Proc. of the IEEE International Symposium on Intelligent Control, 2015: 59-64.
17	陈丽, 陈洋, 杨艳华. 面向三维结构视觉检测的无人机覆盖路径规划[J]. 电子测量与仪器学报, 2023, 37 (2): 1- 10.
	CHEN L , CHEN Y , YANG Y H . UAV coverage path planning for 3D structure visual inspection[J]. Journal of Electronic Measurement and Instrumentation, 2023, 37 (2): 1- 10.
18	JUNG S W, SONG S W, YOUN P, et al. Multilayer coverage path planner for autonomous structural inspection of high-rise structures[C]//Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018.
19	TONG H W, LI B, HUANG H, et al. UAV path planning for complete structural inspection using mixed viewpoint genera- tion[C]//Proc. of the 17th International Conference on Control, Automation, Robotics and Vision, 2022: 727-732.
20	ALMADHOUN R, TAHA T, DIAS J, et al. Coverage path planning for complex structures inspection using unmanned aerial vehicle (UAV)[C]//Proc. of the 12th Intelligent Robotics and Applications International Conference, 2019: 243- 266.
21	ALMADHOUN R, TAHA T, GAN D, et al. Coverage path planning with adaptive viewpoint sampling to construct 3D models of complex structures for the purpose of inspection[C]//Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018: 7047-7054.
22	HOU J M , GOEBEL M , HUBNER P , et al. Octree-based approach for real-time 3D indoor mapping using RGB-D video data[J]. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023, 48, 183- 190.
23	舒亮, 张洁, 陈璇, 等. 面向大规模场景的数字孪生模型快速渲染方法[J]. 计算机集成制造系统, 2022, 28 (11): 3664- 3672.
	SHU L , ZHANG J , CHEN X , et al. Fast rendering method of digital twin model for large scale scenes[J]. Computer Integrated Manufacturing Systems, 2022, 28 (11): 3664- 3672.
24	QIAN X L , WU B K , CHENG G , et al. Building a bridge of bounding box regression between oriented and horizontal object detection in remote sensing images[J]. IEEE Trans.on Geoscience and Remote Sensing, 2023, 61, 1- 9.
25	KRIVOCHEN D G . The search for minimal search: a graph-theoretic approach[J]. Biolinguistics, 2023, 17, e9793. doi: 10.5964/bioling.9793
26	DUCHON F , BABINEC A , KAJAN M , et al. Path planning with modified a star algorithm for a mobile robot[J]. Procedia Engineering, 2014, 96, 59- 69. doi: 10.1016/j.proeng.2014.12.098
27	ZHENG J Z , HE K , ZHOU J R , et al. Reinforced Lin-Kernighan-Helsgaun algorithms for the traveling salesman problems[J]. Knowledge-Based Systems, 2023, 260, 110144. doi: 10.1016/j.knosys.2022.110144
28	HU Q K , LIN Z W , FU J Z . A new global toolpath linking algorithm for different subregions with travelling saleman problem solver[J]. International Journal of Computer Integrated Manufacturing, 2022, 35 (6): 633- 644. doi: 10.1080/0951192X.2021.1992667
29	DING Y K, ZHU Q T, LIU X Y, et al. KD-MVS: knowledge distillation based self-supervised learning for multi-view stereo[C]// Proc. of the European Conference on Computer Vision, 2022: 630-646.
30	LOPEZ L , CELLONE F . SfM-MVS and GIS analysis of shoreline changes in a coastal wetland, Parque Costero del Sur biosphere reserve, Argentina[J]. Geocarto International, 2022, 37 (26): 11134- 11150. doi: 10.1080/10106049.2022.2046870

实验场景	(L×W×H)/m	g/m	ε/(°)	α	β	ω
场景1	50×36×15	1.5	30	0.1	0.45	0.000 5
场景2	30×24×10	1.5	30	0.1	0.45	0.004

d_th/m	场景1		场景2
d_th/m	视点数量	覆盖率/%	视点数量	覆盖率/%
4.0	1 486	94.01	431	96.62
3.0	620	93.44	169	96.44
2.0	236	67.74	54	71.88

路径规划算法	场景1 最大覆盖率	场景2 最大覆盖率
本文所提算法	93.44	96.44
SSCPP	92.62	93.51
ASSCPP	90.05	92.97

实验场景	规划算法	算法耗时/s	路径长度/m	视点/个
场景1	本文算法	57.3	377.85	251
	SSCPP	79.9	1 229.14	1 017
	ASSCPP	188.2	835.25	668
场景2	本文算法	28.9	88.05	72
	SSCPP	35.5	118.05	97
	ASSCPP	57.7	150.01	132

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UAV coverage path planning for aircraft surface visual inspection

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