{"title":"移动机器人路径规划的改进蚁群优化算法","authors":"Juanping Zhao, Xiuhui Fu, Ying Jiang","doi":"10.1109/ISA.2011.5873347","DOIUrl":null,"url":null,"abstract":"Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly seen that this tactic loses some feasible paths and even loses optimal path, so a new ants meeting judgment method is proposed in this paper. At the same time pheromone gain is added to allocate initial pheromone reasonably in order to deal with slow searching speed brought by equivalence distributing of initial pheromone. Pheromone mutual leading method is also designed to accelerate optimizing speed. Above designs can accelerate searching speed but maybe put algorithm running into local optima, so chaos disturbance is introduced to help algorithm jumping out local optima. Finally simulation results indicate that the optimal path on which the robot moves can reach safely and rapidly under 2-D environment.","PeriodicalId":128163,"journal":{"name":"2011 3rd International Workshop on Intelligent Systems and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"An Improved Ant Colony Optimization Algorithm for Mobile Robot Path Planning\",\"authors\":\"Juanping Zhao, Xiuhui Fu, Ying Jiang\",\"doi\":\"10.1109/ISA.2011.5873347\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly seen that this tactic loses some feasible paths and even loses optimal path, so a new ants meeting judgment method is proposed in this paper. At the same time pheromone gain is added to allocate initial pheromone reasonably in order to deal with slow searching speed brought by equivalence distributing of initial pheromone. Pheromone mutual leading method is also designed to accelerate optimizing speed. Above designs can accelerate searching speed but maybe put algorithm running into local optima, so chaos disturbance is introduced to help algorithm jumping out local optima. Finally simulation results indicate that the optimal path on which the robot moves can reach safely and rapidly under 2-D environment.\",\"PeriodicalId\":128163,\"journal\":{\"name\":\"2011 3rd International Workshop on Intelligent Systems and Applications\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 3rd International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISA.2011.5873347\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 3rd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISA.2011.5873347","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Improved Ant Colony Optimization Algorithm for Mobile Robot Path Planning
Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly seen that this tactic loses some feasible paths and even loses optimal path, so a new ants meeting judgment method is proposed in this paper. At the same time pheromone gain is added to allocate initial pheromone reasonably in order to deal with slow searching speed brought by equivalence distributing of initial pheromone. Pheromone mutual leading method is also designed to accelerate optimizing speed. Above designs can accelerate searching speed but maybe put algorithm running into local optima, so chaos disturbance is introduced to help algorithm jumping out local optima. Finally simulation results indicate that the optimal path on which the robot moves can reach safely and rapidly under 2-D environment.