求解路径规划问题的细菌觅食——蚁群算法  

Bacterial forage-ant colony algorithm for path planning problem

作　　者：邢立宁 卢泓宇 马超[3] XING Lining;LU Hongyu;MA Chao(Hangzhou Research Institute,Xidian University,Hangzhou,Zhejiang,China 311231;School of Mechanical and Electrical Engineering and Automation,Foshan University of Science and Technology,Foshan,Guangdong,China 528225;School of Digital Media,Shenzhen Institute of Information Technology,Shenzhen,Guangdong,China 518172)

机构地区：[1]西安电子科技大学杭州研究院,浙江杭州311231 [2]佛山科学技术学院机电工程与自动化学院,广东佛山528225 [3]深圳信息职业技术学院数字媒体学院,广东深圳518172

出　　处：《深圳信息职业技术学院学报》2024年第2期47-54,共8页Journal of Shenzhen Institute of Information Technology

基　　金：陕西省科技创新团队项目(项目编号:2023-CX-TD-07);广东高校重点领域专项项目(项目编号:2021ZDZX1019);广东省普通高校创新团队及特色创新项目(项目编号:2020KCXTD040,2020KTSCX302)。

摘　　要：随着科技的迅速发展,蚁群算法的应用范围越来越广泛,其路径规划的速度以及路线准确度对算法要求越来越高。目前已有的蚁群算法所拥有的收敛性慢容易陷入局部最优问题,为了提高算法的准确度与速度,通过引用细菌觅食算法中的复制与趋向对其进行改进,提高此算法以期提高蚁群算法的效率及其准确率,优化全局搜索能力,并满足多种约束条件下的需求。实验结果表明:细菌觅食算法能够有效地解决一些蚁群算法上的缺陷,提高了蚁群算法的路径规划及其寻优能力且优于其他算法对蚁群算法的改进,证实了改进后的蚁群算法适应多种条件,路径求解的精度明显优于之前未改进的算法。With the rapid development of science and technology,the application range of ant colony algorithm is more and more extensive,and the speed of path planning and the accuracy of route are more and more demanding for the algorithm.The existing ant colony algorithm has slow convergence and is prone to fall into local optimal problems.In order to improve the accuracy and speed of the algorithm,it is improved by referencing the replication and trend in bacterial foraging algorithm,which improves the efficiency and accuracy of the algorithm,optimizes the global search ability,and meets the needs under various constraints.The experimental results show that bacterial foraging algorithm can effectively solve some defects in ant colony algorithm,improve the path planning and optimization ability of ant colony algorithm,and is superior to other algorithms for improving ant colony algorithm.It confirms that the improved ant colony algorithm adapts to various conditions,and the accuracy of path solving is significantly better than that of the previous unimproved algorithm.

关 键 词：路径规划 无人驾驶 蚁群算法 细菌觅食算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]