基于二次A算法的复杂环境下车辆导航路径规划方法

Vehicle Navigation Path Planning Method Based on the Quatratic A Algorithm in Complex Environment

在部队作战或演习中,复杂且未知的野外环境给作战车辆的路径规划造成了极大的影响。针对车辆无法在环境信息未知的复杂野外环境下快速到达目的地的问题,通过改进搜索策略来提高车辆的机动性,同时提出一种加入预处理的二次A*算法来提高车辆实时避障的能力。首先,针对A*算法的搜索策略进行改进;其次,通过预处理算法明确目标区域的环境信息,规划得到全局最优路径,当行进过程中突然出现未知障碍物时,根据车辆的实时位置以及障碍物确定局部规划区域,再一次应用A*算法进行局部最优路径规划;最后,进行实验验证。实验结果表明,车辆在不同地形条件的行驶过程中尽管牺牲了一部分搜索时间和路径长度,但行驶时间分别减少了26.6%、29.5%、32.4%和35.2%。随着地形条件的复杂程度不断变大,算法使车辆的行驶时间减少更多,极大地提高了车辆的机动性,具有重要的现实意义。

In army combats or military exercises,the complex and unknown field environment has a great impact on the path planning of combat vehicles.In view of the problem that the vehicles can not reach its destination quickly in the complex field environment where the environment information is unknown,the maneuverability of vehicles is enhanced by improving the search strategy,and a quatratic A algorithm added with preprocessing is proposed to improve the ability of vehicles to avoid obstacles in real time.Firstly,the search strategy of the A algorithm is improved;secondly,the global optimal path is planned by clarifying the environmental information of the target area by means of preprocessing algorithm.When an unknown obstacle suddenly appears during the journey,the local planning area is determined based on the real-time position of the vehicle and the obstacle,and the local optimal path is then planned by using the A algorithm again;experiments are carried out for verification in the end.The experimental results show reduction of travel time by 26.6%,29.5%,32.4%and 35.2%respectively,although some search time and path length were sacrificed during the driving route of vehicles in different terrain conditions.With the increasing complexity of terrain conditions,this algorithm can greatly reduce the driving time and improve the maneuverability of vehicles,which has important practical significance.