基于改进人工蚁群的智能巡线机器人路径规划  

Path Planning of Intelligent Inspection Robot Based on Artificial Ant Colony

作　　者：刘二根 谭茹涵[1,2] 陈艺琳 郭力 Liu Ergen;Tan Ruhan;Chen Yilin;Guo Li(School of Science,East China Jiaotong University,Nanchang 330013,China;SEC Institute,East China Jiaotong University,Nanchang 330013,China)

机构地区：[1]华东交通大学理学院,江西南昌330013 [2]华东交通大学系统工程与密码学研究所,江西南昌330013

出　　处：《华东交通大学学报》2020年第6期103-107,共5页Journal of East China Jiaotong University

基　　金：国家自然科学基金项目(11761033);江西省教育厅科技项目(GJJ180323);江西省学位与研究生教育教学改革研究项目(JXYJG-2018-095)。

摘　　要：针对智能巡线机器人寻找最优路径的问题,对传统蚁群寻路算法加以改进,利用A*算法改进蚂蚁的寻路规则,且对寻出的路径进行多次平滑迭代,填补了传统A*算法易陷入“陷阱”的缺陷,同时也达到了路径平滑和路程缩短的目的。优化蚁群的信息素处理方法,引入双信息素策略,最终得到最优路径。与传统蚁群算法相比,此方案能准确绕开障碍物,且具有更快、更好的搜索最优路径的能力。In order to find the optimal path for the intelligent inspection robot,the traditional ant colony algorithm was improved.The A*algorithm was used to improve the ant’s path-finding rules,and multiple smooth iterations were performed on the found path,which filled the defects that the traditional A*algorithm easy to fall into a"trap".At the same time,the purpose of smoothing the path and shortening the distance was achieved,the pheromone processing method of ant colony was optimized,and the double pheromone strategy was introduced to get the optimal path.Compared with the traditional ant colony algorithm,the improved algorithm can avoid obstacles accurately,and has a faster and better ability to search for the optimal path.

关 键 词：智能巡线机器人 A*算法 双信息素 蚁群算法 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]