The accuracy of center height detection for corrugated beam guardrails is significantly affected by robot posture in the mobile highway guardrail detection systems based on structured light vision. To address the problem, this paper proposes an integrated calibration method for structured light vision sensors. In the proposed system, the sensor is mounted on a crawler-type mobile robot, which scans and measures the center height of guardrails while in motion. However, due to external disturbances such as uneven road surfaces and vehicle vibrations, the posture of the robot may deviate, causing displacement of the sensor platform and resulting in spatial 3D measurement errors. To overcome this issue, the system integrates inertial measurement unit (IMU) data into the sensor calibration process, enabling real-time correction of posture deviations through sensor fusion. This approach achieves a unified calibration of the structured light vision system, effectively compensates for posture-induced errors, and enhances detection accuracy. A prototype was developed and tested in both laboratory and real highway environments. Experimental results demonstrate that the proposed method enables accurate center height detection of guardrails under complex road conditions, significantly reduces posture-related measurement errors, and greatly improves the efficiency and reliability of traditional detection methods.
A 2025 study studied this question.