{"title":"Robot path planning based on A*algorithm and genetic algorithm","authors":"Tang Xiang Rong, Xu Hong Mei","doi":"10.1109/ICCEIC51584.2020.00028","DOIUrl":null,"url":null,"abstract":"The traditional algorithm of path planning is slow in time, heavy in calculation and large in storage space. Taking the medical service robot of Raytheon hospital(in Wuhan) as an example, optimizing its path planning, this paper proposes a combination algorithm based on genetic algorithm and A* algorithm, and two-dimensional modeling of the hospital map was carried out by raster method. Through simulation experiments, comparison with traditional algorithm and model tests, the feasibility and effectiveness of the combined algorithm are confirmed. Meanwhile, the efficiency of path planning is improved, the step size is optimized by 23%, the time is increased by 135%, and the calculation amount is reduced, and the calculation time and storage space are reduced.","PeriodicalId":135840,"journal":{"name":"2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computer Engineering and Intelligent Control (ICCEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEIC51584.2020.00028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The traditional algorithm of path planning is slow in time, heavy in calculation and large in storage space. Taking the medical service robot of Raytheon hospital(in Wuhan) as an example, optimizing its path planning, this paper proposes a combination algorithm based on genetic algorithm and A* algorithm, and two-dimensional modeling of the hospital map was carried out by raster method. Through simulation experiments, comparison with traditional algorithm and model tests, the feasibility and effectiveness of the combined algorithm are confirmed. Meanwhile, the efficiency of path planning is improved, the step size is optimized by 23%, the time is increased by 135%, and the calculation amount is reduced, and the calculation time and storage space are reduced.