Automated Repair of Road Cracks Based on Mobile Robot Vision Control

Document Type

Article

Publication Date

2026

Department

Department of Civil, Environmental, and Geospatial Engineering

Abstract

Automated pavement crack repair offers a promising approach to significantly extend road lifespan and is crucial for intelligent road maintenance. To tackle challenges associated with real-time crack trajectory extraction and substantial sealing errors, the Automated Pavement Crack Sealing Robot (APCSbot) was developed. APCSbot integrates a real-time crack trajectory segmentation network (S2TNet) and a cross-entropy-based adaptive fuzzy control method (CEAFC) for crack sealing repair. The S2TNet incorporates Anchor Ratio IoU Sampling (ARIS) and Balanced Fine-Grained Features (BFGF) to enhance the detector’s capability in predicting bounding boxes and segmenting instance binary masks, consequently improving crack trajectory extraction accuracy. The CEAFC method employs cross-entropy optimization iterations to tune controller parameters and constructs fuzzy logic to enhance repair control robustness. Furthermore, an unmanned wheeled robot framework based on four-wheel independent differential drive was established, integrating the crack segmentation network and tracking repair control methods. Extensive experiments conducted on DeepCrack, CFD, and S2T-Crack datasets demonstrate a real-time pavement crack segmentation accuracy of 80. 21%. The crack sealing repair process achieves a speed of approximately 0.05 m · s−1, with an average sealing error for slender cracks of 5. 17 mm. The APCSbot showcases its accuracy and robustness in pavement crack sealing repair, thus providing technical support for intelligent road maintenance.

Publication Title

Zhongguo Gonglu Xuebao China Journal of Highway and Transport

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