CLC number: TP212

The Calibration Method of Line Structured Light Sensor for Integrated Position and Pose Detection of Highway Guardrail Inspection Robots

用于高速公路护栏检测机器人一体化位姿检测的线结构光传感器标定方法

¹ Research Institute of Highway Science, Ministry of Transport, Beijing 100088, China
² School of Information Engineering, Chang'an University, Xi'an 710064, Shaanxi, China
³ School of Electronic and Control Engineering, Chang'an University, Xi'an 710064, Shaanxi, China

Received: 18 December 2024

Abstract

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.

摘要

为了解决在基于结构光视觉的移动式公路护栏检测系统中，机器人姿态对波形梁护栏中心高度检测精度造成显著影响的问题，本文提出了一种结构光视觉传感器的集成标定方法。在所提出的系统中，传感器安装在履带式移动机器人上，机器人在运动过程中对护栏进行扫描和测量，以获取其中心高度。然而，由于不平整路面和车辆振动等外部干扰因素，机器人姿态可能发生偏移，导致传感器平台发生位移，从而产生三维空间测量误差。为解决这一问题，系统将惯性测量单元(IMU)的数据集成到传感器标定过程中，通过传感器融合实现实时姿态偏差校正。该方法实现了结构光视觉系统的统一标定，有效补偿了姿态引起的误差，提高了检测精度。本文开发了系统原型，并在实验室和真实高速公路环境中进行了测试。实验结果表明，所提出的方法在复杂道路条件下能够实现护栏中心高度的高精度检测，显著降低姿态相关测量误差，大幅提升了传统检测方法的效率与可靠性。