{"title":"Relevant positioning of a mobile robot using a particle filter design approach","authors":"Takoua Grami, A. Tlili","doi":"10.1109/IC_ASET49463.2020.9318257","DOIUrl":null,"url":null,"abstract":"The present paper proposes a new framework based on a python code using the particle filter approach to monitor and estimate accurately the positions and the directions of a mobile robot. As a matter of fact, the real time localization of such a mobile robot is a challenging task due to diversified uncertainties and temporal changes in the environmental circumstances, measurement noises as well as errors of sensors used for anticipating the trajectory. The efficacy and the outstanding performances of the proposed particle filter-based real time localization approach are demonstrated via numerical simulation on an intelligent autonomous mobile robot with a considerable developed python code.","PeriodicalId":250315,"journal":{"name":"2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC_ASET49463.2020.9318257","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 present paper proposes a new framework based on a python code using the particle filter approach to monitor and estimate accurately the positions and the directions of a mobile robot. As a matter of fact, the real time localization of such a mobile robot is a challenging task due to diversified uncertainties and temporal changes in the environmental circumstances, measurement noises as well as errors of sensors used for anticipating the trajectory. The efficacy and the outstanding performances of the proposed particle filter-based real time localization approach are demonstrated via numerical simulation on an intelligent autonomous mobile robot with a considerable developed python code.