基于异源信息融合的无人水面艇动态路径规划

Dynamic path planning for unmanned surface vehicle based on heterologous information fusion

为解决无人水面艇自主避碰决策中的动态路径规划问题,提出一种基于电子海图与雷达图像融合环境建模的改进人工势场动态路径规划方法.对电子海图中静态环境数据和动态雷达图像数据进行提取,采用Hausdorff距离匹配算法对异源信息进行融合,建立无人水面艇路径搜索空间的动态环境模型,并在动态感知环境信息的基础上,利用改进的人工势场法进行路径规划的仿真验证.仿真结果证明了基于电子海图与雷达图像信息融合的无人艇动态路径规划方法的合理性和有效性.

In order to solve the dynamic path planning problem in autonomous collision avoidance decision of unmanned surface vehicle（USV）,an improved artificial potential field dynamic path planning method based on heterologous information fusion was proposed. By extracting the static environment data from electronic chart and dynamic data from radar image,the Hausdorff distance matching algorithm was used to fuse the heterogeneous information, and the dynamic environment model for path search of unmanned surface vehicle was established. Based on the environmental model,the improved artificial potential field method was used to simulate the path planning. Simulation results show the rationality and effectiveness of the USV dynamic path planning method based on the integration of electronic chart and radar image information.