Model identification of a Marine robot in presence of IMU-DVL misalignment using TUKF

Abstract In today’s world, control and navigation of autonomous underwater vehicles (AUVs) are quite challenging issues. In these fields, obtaining an identified dynamic model of AUV is a vital part. In this paper, a method for parameter estimation of an AUV planar model is proposed, which uses augmented state space technique and Square Root Transformed Unscented Kalman Filter (SR-TUKF) as an estimator. Furthermore, by modeling, misalignment between Inertial Measurement Unit (IMU) and Doppler Velocity Log (DVL) is estimated, simultaneously. Parameter identification is conducted using data of an AUV, equipped with Gyroscope, DVL and Encoder for measuring control inputs, in a planar maneuver. According to the experimental results, the output of the identified model has matched appropriately to the output of sensors in validation maneuvers. With and without considering the estimated misalignment between IMU-DVL, navigation is performed by fusing inertial navigation system (INS) with DVL. The results show an improvement in the end point error with respect to the travel distance by 53 percent in a maneuver with a distance of 6557 meters. Therefore, the proposed method for estimation of a planar model of AUV and misalignment of sensors has a plausible result, experimentally verified by raw data of a simple maneuver.