Research on Feature Identification and Trajectory Planning of Pavement Cracks

As the most common method to detect pavement cracks, manual detection has uncontrollable factors such as low efficiency, inconsistent standards and easy be interfered with by external forces, so it is not suitable for crack in today’s intricate traffic network. In order improve efficiency of repair reduce labor cost process, this paper proposes an intelligent algorithm. The algorithm uses image numerical parameters classify cracks different geometric features extracts texture various types based on filtering strategies. It solves problem that traditional single algorithms are difficult extract according characteristics collected image, which leads loss information. Finally, establishes a mathematical model efficient trajectory planning combined nozzle size crack-repairing machine. paper, robustness test carried out dataset experiment prototype, verifies accuracy reliability planned trajectory.