Feature Detection and Classification in Buried Pipes using LiDAR Technology

Buried infrastructure presents unique challenges for autonomous robotic inspection due to its confined geometry and the structural variations within pipe networks. While CCTV is widely used for pipe inspection, LiDAR sensors offer complementary advantages, including precise ranging capabilities and accurate depth perception. In this work, we introduce a low-cost LiDAR-based system designed to detect blockages and accurately identify critical structural features - such as joints, manholes, and other discontinuities - within these environments in real-time. By combining robust data acquisition, efficient processing, and clear decision-making criteria, the approach enhances the effectiveness, reliability, and automation of underground inspections.