【摘要】 针对地面无人平台协同作战时路径规划问题,提出了一种优化型的蚁群算法以寻求战时最佳进攻路线.通过优化传统蚁群算法,模拟了单平台的路径规划并获得各参数的稳定值,进而将其结果拓展到多机协同作战模式下,以获得各平台由起始点到目标点的最优路径.为更加真实地体现出战场环境,在路径规划中提出了战术规避的策略并在2种不同环境模型下验证了算法的实用性.结果表明,优化型蚁群算法相比于传统蚁群算法在迭代次数方面提高了64.2%,搜索路径长度方面提高了57.5%.更多还原

【Abstract】 To investigate the strategy of path planning for cooperative operation of unmanned ground platform,an optimized ant colony algorithm was proposed to find the best attack route in wartime.The path planning of the single platform was simulated and the stable values of each parameters were obtained by optimizing the traditional ant colony algorithm,these results were extend to the coordinated operation of multi-machine and the optimal path of platform from the starting point to the target point was obtained.In order to reflect the battlefield environment more realistically,the tactical avoidance strategy was proposed in the path planning and the practicability of the algorithm was verified under two different environment models.The results show that the optimized ant colony algorithm improves the number of iterations by 64.2%and the search path length by 57.5% compared with the traditional ant colony algorithm.更多还原