| For the rapid observation problem in the ocean front, a front tracking algorithm based on temperature dynamic estimation for autonomous underwater vehicle (AUV) is proposed. Firstly, Gauss process regression (GPR) is chosen as the estimation tool of environmental model to estimate the temperature in the vicinity of AUV. Next, the current observation position of AUV is determined, and the tracking strategy along the gradient direction is implemented in the front area, and the isotherm tracking strategy is implemented in the front area boundary. Finally, according to the temperature prediction results, this algorithm guides the selection of observation path points under different path planning strategies, and realize the online path planning of AUV. In this paper, this algorithm is used to simulate the frontal observation area simulated by satellite remote sensing data. The results show that compared with the conventional method, this algorithm can complete the task of front tracking quickly, and has good adaptability to the environment, and can meet the observation requirements of different frontal forms. |
