基于灰色预测的农业机器人GPS导航系统硬故障隔离

Hard Fault Isolation of GPS Navigation System Based on Gray Prediction for Agricultural Robot

采用卡方检验和灰色预测相结合的算法,综合利用卡尔曼滤波数据和GPS历史有效定位数据,在不增加额外传感器信息条件下,对农业机器人导航中常见的GPS定位数据突变故障进行了检测和隔离。实验结果表明,这类故障被有效隔离后,不会影响导航系统的正常工作。GPS定位数据的灰色预测残差小于10 cm,当虚警率仅为0.05时仍可降低卡方故障检验的漏检率。

By combining the chi-square test and gray prediction,an algorithm of hard fault detection and isolation was introduced for the navigation of agricultural robot.The Kalman filtered data and historical valid GPS data were applied to detect and isolate positioning fault caused by the GPS failure,and none of other sensors were applied.With the prototype of the agricultural wheeled mobile robot,the experimental results showed that the GPS positioning fault was isolated effectively and had no any effects on the robot navigation.The error of gray prediction of GPS positioning data were less than 10cm,and the missing rate of fault detection was reduced further when the false alarm rate of the chi-square test method was only 0.05.