Author(s)

JiaYi Zeng^*, ZhengYu Zhong, SiQi Wang, BoYu Xu, RunLin Chen

Affiliation(s)

School of Aviation, Beijing Institute of Technology, Zhuhai 519000, Guangdong, China.

Corresponding Author

JiaYi Zeng

ABSTRACT

The increasing demand for intelligent monitoring in engineering and construction has highlighted several limitations within current Unmanned Aerial Vehicle (UAV) technologies. These challenges include inadequate flight endurance, restricted payload capacity, and a reliance on continuous manual control—particularly evident in tasks requiring reliable adhesion and autonomous operation in the assessment of vertical structures and high-altitude hazardous environments. To mitigate these issues, the present project proposes the development of a lightweight adsorption-capable UAV, designed to achieve attitude reversal during flight and to adhere to both horizontal and vertical surfaces of structures for the purposes of site surveying, monitoring, and data collection. This research details the design and production of a functional prototype of the adsorption UAV, which addresses the aforementioned deficiencies by enhancing endurance, increasing payload capability, and reducing dependence on manual intervention. This innovative solution offers significant advancements in automated monitoring capabilities within complex operational environments.

KEYWORDS

Adsorption; Unmanned aerial vehicles; Flight control; Lightweight design

CITE THIS PAPER

JiaYi Zeng, ZhengYu Zhong, SiQi Wang, BoYu Xu, RunLin Chen. Design and implementation of lightweight adsorption UAVs. Journal of Computer Science and Electrical Engineering. 2025, 7(4): 1-5. DOI: https://doi.org/10.61784/jcsee3061.

REFERENCES

[1] Vergouw B, Nagel H, Bondt G, et al. Drone technology: Types, payloads, applications, frequency spectrum issues and future developments. The future of drone use: Opportunities and threats from ethical and legal perspectives, 2016: 21-45.

[2] Budiharto W, Irwansyah E, Suroso J S, et al. Mapping and 3D modelling using quadrotor drone and GIS software. Journal of Big Data, 2021, 8: 1-12.

[3] Guo Q, Yang Z, Xu J, et al. Progress, challenges and trends on vision sensing technologies in automatic/intelligent robotic welding: State-of-the-art review. Robotics and computer-integrated manufacturing, 2024, 89: 102767.

[4] Deliry S I, Avdan U. Accuracy of unmanned aerial systems photogrammetry and structure from motion in surveying and mapping: a review. Journal of the Indian Society of Remote Sensing, 2021, 49(8): 1997-2017.

[5] Oosedo A, Abiko S, Narasaki S, et al. Flight control systems of a quad tilt rotor unmanned aerial vehicle for a large attitude change//2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2015: 2326-2331.

[6] Grisetti G, Kümmerle R, Stachniss C, et al. A tutorial on graph-based SLAM. IEEE Intelligent Transportation Systems Magazine, 2010, 2(4): 31-43.

[7] Chetverikov D, Svirko D, Stepanov D, et al. The trimmed iterative closest point algorithm//2002 International Conference on Pattern Recognition. IEEE, 2002, 3: 545-548. 

[8] Tian J M. Structural Design and Research of a Vacuum Adsorption-Based Wall Cleaning Robot. Southwest Jiaotong University, 2013.

[9] Lai Q S. Design of an Unmanned Aerial Vehicle System Based on the MAVLink Protocol. Hangzhou Dianzi University, 2017.

[10] Qin C. Drone Image Matching Point Cloud Filtering Processing and 3D Reconstruction. Southwest Jiaotong University, 2015.

[11] Dong W, Mao G, Zhang H D, et al. Research on Small Deformation Initial Value Estimation Based on SIFT Feature Matching. Laser Technology, 2025: 1-12. http://kns.cnki.net/kcms/detail/51.1125.TN.20250407.1242.002.html.

[12] Wang Z Z, Zhang S, Ning C, et al. An Image Feature Point Matching Algorithm Based on Improved SURF. Hebei Industrial Science and Technology, 2024, 41(06): 418-425.

[13] Hu Q S, Li J W, Zhang Y S, et al. IMU and LiDAR Fusion SLAM Technology for Unmanned Mining Vehicles. Mining and Industrial Automation, 2024, 50(10): 21-28. DOI: 10.13272/j.issn.1671-251x.18209.

[14] Dai J L, Chen Z Y, Ye X Z. Application of the ICP Algorithm in Point Cloud Registration . Journal of Image and Graphics, 2007(03): 517-521.

[15] Chen Y, Wang Q, Peng X, et al. Flow field and sealing performance analysis of compliant foil face gas seal. Advances in Mechanical Engineering, 2022, 14(6): 1687132221108488.