抄録
The total length of sewer pipelines in Japan is over 440,000 kilometers. Until now, visual inspection by experienced staff members have been carried out to watch in-pipes animation images which are obtained from an autonomous vehicle equipped with a CCD camera. Quantitative measurement methods for regularly scheduled inspection of those pipelines have been desired instead. In this study, we developed vehicles equipped with an inertial navigation system (INS) consists of a gyro sensor and an accelerometer, so that we can measure unevenness of the sewer pipe accurately and quantitatively. We also aim to achieve a simple measurement scheme at comparatively low cost. To accomplish these missions, two vehicles are designed and manufactured respectively. The first vehicle is designed for the function of driving to drag a second vehicle. The second vehicle has only a function of measurement to be towed and does not move independently. We use the MEMS sensor devices installed on the second vehicle to suit our particular needs which have their low cost and small sizes. However, they are notorious for their accuracy such as drift error in the gyro sensor. We apply the extended Kalman filter (EKF) algorithm to reduce the estimation errors by using the data of gyro sensor and accelerometer. We use Quaternion as state variables of the attitude for its coordinate system. The experimental study shows that the suggested algorithms effectively remove the errors and it can lead to systematic measurement schemes to accurately obtain the unevenness of the sewer pipes.