摘要
为提高路径规划效率,避免蚁群算法输出非最优路径,构建一种多智能体路径规划模型。使用栅格法建立智能体环境感知模型,改进蚁群算法中局部和全局信息素更新规则,通过调节转弯次数和信息素浓度约束蚂蚁行进。令算法能智能地放大或减少路径中信息素浓度。当迭代次数达到设置的最大迭代次数时,输出值即为最优路径规划结果。经实验证明,改进算法获得的规划路径较短,迭代收敛速度较快。
To improve the efficiency of path planning and avoid ant colony algorithm outputting non optimal paths,a multi-agent path planning model is proposed.The grid method is used to establish the environment awareness model of agents,improving the local and global pheromone update rules in the ant colony algorithm,and constraining the ants to travel by adjusting the number of turns and pheromone concentration.The algorithm can intelligently enlarge or reduce the pheromone concentration in the path.When the number of iterations reaches the set maximum,the output value is the optimal path planning result.Experimental results have shown that the improved algorithm achieves shorter planning paths and faster iterative convergence speed.
作者
李伟东
王冠涵
LI Weidong;WANG Guanhan(School of Mechanical Engineering,Dalian University of Technology,Dalian 116081,China)
出处
《吉林大学学报（信息科学版）》
CAS
2024年第4期654-661,共8页
Journal of Jilin University（Information Science Edition）
基金
辽宁省科技创新重大专项基金资助项目(ZX20220560)。
关键词
改进蚁群算法
多智能体
栅格法
环境感知
信息素更新
improve ant colony algorithm
multi agent
grid method
environmental perception
pheromone update
