{"title":"Indoor Navigation System of Mobile Robot with Trajectory Optimization","authors":"Qishuai Liu, Yu-rou Jiang, Ying Li","doi":"10.1109/MMAR55195.2022.9874287","DOIUrl":null,"url":null,"abstract":"This paper proposes a navigation system for mobile robot working in indoor environment, which includes mapping and trajectory generation for the motion tracking problem of the real mobile robot. The mapping process comprises a Gaussian model to improve the accuracy of the environment representation. With this new mapping method, the mobile robot knows the obstacle in the environment around robot itself. For the trajectory generation process, a multimodality method is used to explore all feasible paths to reach the target point by estimating the density of distribution of the objective function. Finally, the experiments show the effectiveness of this navigation framework.","PeriodicalId":169528,"journal":{"name":"2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR55195.2022.9874287","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
This paper proposes a navigation system for mobile robot working in indoor environment, which includes mapping and trajectory generation for the motion tracking problem of the real mobile robot. The mapping process comprises a Gaussian model to improve the accuracy of the environment representation. With this new mapping method, the mobile robot knows the obstacle in the environment around robot itself. For the trajectory generation process, a multimodality method is used to explore all feasible paths to reach the target point by estimating the density of distribution of the objective function. Finally, the experiments show the effectiveness of this navigation framework.