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This paper presents a collaborative inspection approach for large-scale urban sewer pipe networks using multiple robotic pipe capsules (RPCs) integrated with lightweight deep learning and spatial optimization. The method features a bi-level network for coordinating the movements of workers and RPCs, enabling real-time fault detection with a balanced accuracy of 83.43%. The proposed system addresses the inefficiencies of traditional inspection methods and enhances coverage in complex urban environments.

Author

geliao233

Language

EN