{"title":"Rapid navigation function control for omnidirectional mobile platform","authors":"W. Kowalczyk, M. Przybyla, K. Kozlowski","doi":"10.1109/MMAR.2017.8046812","DOIUrl":null,"url":null,"abstract":"This paper presents an extension of navigation function used to control an omnidirectional robot. Navigation function is used to control position coordinates while the orientation variable is controlled with simple proportional controller. The extension relies on a specific normalization of navigation function gradient. Presented method results in much more rapid convergence in comparison to classic approach based on negative gradient of the navigation function. The most noticeable result of the extension is observed for high values of κ parameter, which must be increased if the distances between obstacles are small. Experimental results are given to illustrate effectiveness of the proposed algorithm.","PeriodicalId":189753,"journal":{"name":"2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMAR.2017.8046812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This paper presents an extension of navigation function used to control an omnidirectional robot. Navigation function is used to control position coordinates while the orientation variable is controlled with simple proportional controller. The extension relies on a specific normalization of navigation function gradient. Presented method results in much more rapid convergence in comparison to classic approach based on negative gradient of the navigation function. The most noticeable result of the extension is observed for high values of κ parameter, which must be increased if the distances between obstacles are small. Experimental results are given to illustrate effectiveness of the proposed algorithm.