基于多传感信息融合的轨道线形检测

Study on the Detection of Linear Track based on Multi - Sensor Information Fusion

摘要:

多传感信息融合是实现轨道线形高精度检测的重要方法,而加速度计和陀螺仪是多传感信息融合中的关键传感器。为了解决加速度计和陀螺仪存在累积误差导致测量精度较低的问题,提出一种基于多传感信息融合的轨道线形检测方法。基于捷联惯性系统和双目视觉的测量原理,建立了双目视觉与惯性测量结合的多传感数据融合模型,并利用扩展卡尔曼滤波实现了双目视觉、加速度计和陀螺仪测量信息的融合,提高轨道线形检测精度。通过实验进行验证,结果表明：基于多传感信息融合方法的测量精度比惯性测量方法提高了近9倍,且测量所得坐标在三个方向上的最大位移绝对误差不超过0.536mm,可有效实现高精度轨道线形检测。

Abstract:

Multi-sensor information fusion is an important method of high-precision track detection, and accelerometer and gyroscope are the key sensors in multi-sensor information fusion. In order to solve the problem of low measurement accuracy caused by the accumulative error of accelerometer and gyroscope, a method of track line detection based on multi-sensor information fusion is proposed. Based on the measurement principle of strapdown inertial system and binocular vision, a multi-sensor data fusion model combining binocular vision, gyroscope and accelerometer is established, and the integration of binocular vision, accelerometer and gyroscope measurement information is realized by using extended kalman filter to improve the accuracy of track line detection. The experimental results show that the measurement accuracy based on the multi-sensor fusion method is nearly 9 times higher than that of the inertial method, the maximum displacement error of the measured coordinates in the three directions is no more than 0.536mm,which can realize the high-precision track line shape detection.