{"title":"Path Planning of Robot Based on Rough Sets and Ant Colony Algorithm","authors":"Zhang Li","doi":"10.1109/ICECC.2012.615","DOIUrl":"https://doi.org/10.1109/ICECC.2012.615","url":null,"abstract":"The mobile robot path planning problem is a very challenging problem in robotics.In this paper,hybrid method of rough sets and Ant Colony Algorithm is presented to raise the speed and accuracy of path planning of robot.Firstly,the decision rules are obtained based on rough set theory,and the initial table is established and is simplified according to the rough set theory.Secondly the minimal decision table from which the minimal decision rules are drawn is obtained finally.And then a series of available paths are produced by training the obtained minimal decide rule.Finally,the population of paths is optimized by using ant colony algorithms,and simulations are done in a raster environment,and the excellent path is got.And compare with the basic ant colony algorithm,simulation results show that the improved algorithm is simple and effective,convergence is fast and has good search capability,and also show that the hybrid method is available in raising the speed of path planning of robot.","PeriodicalId":204214,"journal":{"name":"Computer and Digital Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114970937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}