{"title":"An Improved A* Path Planning Algorithm for Indoor Intelligent Robot","authors":"Shiyun Qian, Yajie Ma, Doudou Hong","doi":"10.1145/3366715.3366718","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce an improved A* path planning algorithm for indoor intelligent robot. Aiming at the problem of intelligent robot car path planning in complex indoor environment with obstacles such as wall. Firstly, the indoor environment is divided into grids and we can get the connected topology. The connectivity between grids is characterized by adjacency matrices. Then we study the influence of different heuristic functions on the efficiency of path planning algorithm. Based on the traditional A* algorithm, the direction factor is introduced. Moreover we also consider the impact of distance and direction on search efficiency. Finally, the algorithm is simulated by Matlab. The experimental results show that compared with the traditional A* algorithm, the proposed algorithm has a significant improvement in path search efficiency.","PeriodicalId":425980,"journal":{"name":"Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19","volume":"12 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 International Conference on Robotics Systems and Vehicle Technology - RSVT '19","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3366715.3366718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we introduce an improved A* path planning algorithm for indoor intelligent robot. Aiming at the problem of intelligent robot car path planning in complex indoor environment with obstacles such as wall. Firstly, the indoor environment is divided into grids and we can get the connected topology. The connectivity between grids is characterized by adjacency matrices. Then we study the influence of different heuristic functions on the efficiency of path planning algorithm. Based on the traditional A* algorithm, the direction factor is introduced. Moreover we also consider the impact of distance and direction on search efficiency. Finally, the algorithm is simulated by Matlab. The experimental results show that compared with the traditional A* algorithm, the proposed algorithm has a significant improvement in path search efficiency.