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Article

Gecko-Inspired Robots for Underground Cable Inspection: Improved YOLOv8 for Automated Defect Detection

by
Dehai Guan
1,2 and
Barmak Honarvar Shakibaei Asli
2,*
1
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
Centre for Life-Cycle Engineering and Management, Faculty of Engineering and Applied Sciences, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UK
*
Author to whom correspondence should be addressed.
Electronics 2025, 14(15), 3142; https://doi.org/10.3390/electronics14153142
Submission received: 12 July 2025 / Revised: 29 July 2025 / Accepted: 4 August 2025 / Published: 6 August 2025
(This article belongs to the Special Issue Robotics: From Technologies to Applications)

Abstract

To enable intelligent inspection of underground cable systems, this study presents a gecko-inspired quadruped robot that integrates multi-degree-of-freedom motion with a deep learning-based visual detection system. Inspired by the gecko’s flexible spine and leg structure, the robot exhibits strong adaptability to confined and uneven tunnel environments. The motion system is modeled using the standard Denavit–Hartenberg (D–H) method, with both forward and inverse kinematics derived analytically. A zero-impact foot trajectory is employed to achieve stable gait planning. For defect detection, the robot incorporates a binocular vision module and an enhanced YOLOv8 framework. The key improvements include a lightweight feature fusion structure (SlimNeck), a multidimensional coordinate attention (MCA) mechanism, and a refined MPDIoU loss function, which collectively improve the detection accuracy of subtle defects such as insulation aging, micro-cracks, and surface contamination. A variety of data augmentation techniques—such as brightness adjustment, Gaussian noise, and occlusion simulation—are applied to enhance robustness under complex lighting and environmental conditions. The experimental results validate the effectiveness of the proposed system in both kinematic control and vision-based defect recognition. This work demonstrates the potential of integrating bio-inspired mechanical design with intelligent visual perception to support practical, efficient cable inspection in confined underground environments.
Keywords: cable inspection; gecko-inspired robots; YOLOv8; kinematics; visual detection cable inspection; gecko-inspired robots; YOLOv8; kinematics; visual detection

Share and Cite

MDPI and ACS Style

Guan, D.; Honarvar Shakibaei Asli, B. Gecko-Inspired Robots for Underground Cable Inspection: Improved YOLOv8 for Automated Defect Detection. Electronics 2025, 14, 3142. https://doi.org/10.3390/electronics14153142

AMA Style

Guan D, Honarvar Shakibaei Asli B. Gecko-Inspired Robots for Underground Cable Inspection: Improved YOLOv8 for Automated Defect Detection. Electronics. 2025; 14(15):3142. https://doi.org/10.3390/electronics14153142

Chicago/Turabian Style

Guan, Dehai, and Barmak Honarvar Shakibaei Asli. 2025. "Gecko-Inspired Robots for Underground Cable Inspection: Improved YOLOv8 for Automated Defect Detection" Electronics 14, no. 15: 3142. https://doi.org/10.3390/electronics14153142

APA Style

Guan, D., & Honarvar Shakibaei Asli, B. (2025). Gecko-Inspired Robots for Underground Cable Inspection: Improved YOLOv8 for Automated Defect Detection. Electronics, 14(15), 3142. https://doi.org/10.3390/electronics14153142

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