基于概率势场的无人帆船实时路径规划研究

Research on real-time path planning of unmanned sailing ship based on probability potential field

无人帆船的运动行为受外界风场影响巨大,因此如何规划行进路线,以最快到达目的地,是无人帆船应用中十分重要的难题。为了在可变风场环境下的路径规划中,利用海洋风场所具有的季节性变化规律,以降低航行时间,提出了概率势场(PPF),将风向的规律性变化与其对帆船运动的影响强度相结合,建立空间范围的风向概率势场,在寻求最优路径时,将概率势场作为启发函数的组成因子,以保证算法过程倾向于选择使风向概率势场变大的解。仿真实验表明,与传统实时路径规划算法进行对比,基于概率势场的实时规划算法所得航点,可以提高航行平均速度,显著降低无人船到达目的地所需时间。

The behavior of unmanned sailing boats is greatly affected by the external wind field,so how to plan the travel route to reach the destination as soon as possible is a very important problem in the application of unmanned sailing boats.In order to make use of the seasonal variation law of the ocean wind field in the path planning under the variable wind field environment,the concept of probability potential field is proposed,which combines the regular change of the wind direction with the intensity of its influence on the sailing movement to establish The wind direction probability potential field in the spatial range.When seeking the optimal path,the probability potential field is used as a constituent factor of the heuristic function to ensure that the algorithm process tends to choose a solution that makes the wind direction probability potential field larger.Simulation experiments show that compared with the traditional real-time path planning algorithm,the waypoints obtained by the real-time planning algorithm based on the probabilistic potential field can increase the average sailing speed and significantly reduce the time required for the unmanned ship to reach its destination.