Ye-Chan An, Sunghyeon Joo, Arpan Ghosh, HyunJi Park, Tae-Yong Kuc
{"title":"An UV Sensor Coverage Algorithm with Place Segmentation for Disinfection Robots","authors":"Ye-Chan An, Sunghyeon Joo, Arpan Ghosh, HyunJi Park, Tae-Yong Kuc","doi":"10.1109/ur55393.2022.9826291","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an UV(ultraviolet) sensor coverage algorithm based on occupancy grid maps for complete disinfection. The algorithm is developed to disinfect the environment in which the robots are applied. The nodes for full coverage disinfection are generated using the coordinate average of each node group. The group is clustered with k-means of the random nodes extracted from the grid map. Additionally, we combine place segmentation that allows selective and intensive disinfection by separating the working area. The places are divided by the mean and variance of the disinfection nodes. We demonstrate the algorithm in the various experimental environments.","PeriodicalId":398742,"journal":{"name":"2022 19th International Conference on Ubiquitous Robots (UR)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 19th International Conference on Ubiquitous Robots (UR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ur55393.2022.9826291","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 propose an UV(ultraviolet) sensor coverage algorithm based on occupancy grid maps for complete disinfection. The algorithm is developed to disinfect the environment in which the robots are applied. The nodes for full coverage disinfection are generated using the coordinate average of each node group. The group is clustered with k-means of the random nodes extracted from the grid map. Additionally, we combine place segmentation that allows selective and intensive disinfection by separating the working area. The places are divided by the mean and variance of the disinfection nodes. We demonstrate the algorithm in the various experimental environments.