面向海洋观测的AUV能量最优采样路径规划

Ocean Vessel Trajectory Estimation

以海洋观测为任务目标,以AUV航行能量最优为约束,设计了AUV的采样路径规划方法。首先,利用连续空间填充式采样法快速搜索研究海域的采样点位置,其次,结合采样设计方法得到的采样点位置结果,对AUV的采样路径规划的问题进行描述,设计基于改进粒子群算法的路径规划方法,最后,基于真实海洋地形及海水温度数据,对采样和路径规划方法进行实验验证。

Many conventional ocean navigation systems and Vessel Traffic Management&Reporting Services are equipped with Radar facilities for this purpose.However,the accuracy of the predictions of maneuvering trajectories of vessels depends mainly on the goodness of estimation of vessel position,velocity and acceleration.Hence,this study presents a maneuvering ocean vessel model based on a curvilinear motion model with the measurements based on a linear position model for the same purpose.Furthermore,the system states and measurements models associated with a white Gaussian noise are also assumed.The Extended Kalman Filter is proposed as an adaptive filter algorithm for the estimation of position,velocity and acceleration that are used for prediction of maneuvering ocean vessel trajectory.