Simultaneous localization and tracking algorithm utilizing FastSLAM framework for autonomous underwater vehicles

The cooperative localization is an important research question in the field of Tri-Co Robots study. The scheme of the cooperative localization algorithm depends on the ability of information interaction between the robots. To solve the problem that the cooperative localization accuracy is obviously reduced when the communication is interrupted for a long time between the autonomous underwater vehicles (AUV), the simultaneous localization and tracking (SLAT) algorithms based on the FastSLAM framework are developed in this research, borrowing the principle of the simultaneous localization and mapping (SLAM) algorithms. The master AUV is regarded as a non-cooperative target and a motion estimator used to track the master AUV is built in the slaver AUV. When the motion state of the master AUV is estimated, the improvement of the self localization accuracy of the slaver AUV is achieved, using the relative measurement information obtained from the sonar sensor on the slaver AUV in real time. The simulation experimental results show that the proposed SLATF1.0 and 2.0 algorithms can effectively reduce the localization errors compared to the conventional dead reckoning method under the condition of long-term communication interruption, and the 2.0 algorithm has better adaptability to the influence of the detection accuracy variety. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.