基于模糊化环境建模的无人车路径规划研究

Path planning for unmanned ground vehicle based on fuzzy obstacles environment model

无人作战车在战场环境中的路径规划面临的重要问题之一是对地形的理解,以及不同地形条件下无人车的可通行能力分析。本文提出了一种针对野外战场环境进行模糊化环境建模的方法。该方法能够对野外战场环境中的多种路面模型进行模糊化处理,并根据各路面的通行状况与通行规则定义相应的路面可用度指标以评价路面的可通行能力,建立越野环境模型。利用A*算法进行路径搜索,仿真实验表明,本文算法稳定有效,能满足无人车战场越野路径规划的需要。

A challenge in path planning for military unmanned ground vehicle is to understand the road conditions and analyze the usability of the roads. Based on fuzzy obstacles,an environment modeling approach was presented,and an applicability index was defined to evaluate the locomotive capability of UGV on a road surface according to the road conditions and passing rules. Finally A-star algorithm was used to search the routes. The simulation results show that the presented method is effective and stable,capable of achieving multiple objectives according to different missions.