【摘要】 针对蚁群算法在三维路径规划中存在的搜索效率低,易陷入停滞和局部最优等问题,对蚁群算法进行了改进。首先,根据最优路径的自身特点对初始信息素进行不均匀分配,提高算法初期的搜索效率;其次,在启发函数中引入夹角因素,使算法对于最优路径的搜索更具有方向性,并对信息素和启发函数的权重因子α和β的取值进行动态调整,加快算法收敛速度;最后,对信息素更新规则提出改进,设定迭代阈值,对信息素挥发系数加以完善,避免算法陷入局部最优。通过栅格法对三维环境建模,仿真结果证明了改进后蚁群算法的可行性和有效性。更多还原

【Abstract】 Aiming at the problems of low searching efficiency, easy stagnation and local optimum of ant colony algorithm in three-dimensional(3 D)path planning, an adaptive improvement is proposed for ant colony algorithm.Firstly, according to the characteristics of optimal path, the initial pheromone is unevenly distributed to improve the initial searching efficiency of the algorithm.Secondly, introduce the angle factor in the heuristic function, make the algorithm more directional for the search of the optimal path, and the values of the weight factors α and β of the pheromone and heuristic function are dynamicly adjusted, and accelerate the convergence speed of the algorithm.Finally, the pheromone update rule is improved, the iterative threshold is set, and the pheromone volatilization coefficient is improved to avoid the algorithm falling into local optimum.The three-dimensional environment is modeled by the grid method.The simulation results demonstrate the feasibility and effectiveness of the improved ant colony algorithm.更多还原