{"title":"基于三维生存能力图的UGV最优路径规划算法","authors":"Min-Ho Kim, Min-Cheol Lee","doi":"10.1109/URAI.2013.6677377","DOIUrl":null,"url":null,"abstract":"UGV has widely used in the battlefield, thus UGV's survivability technique has become one of the main issue on the path planning algorithm. In this study, 3D survivability map is suggested for UGV survivability, and the optimal path planning algorithm on this map is also suggested. 3D survivability map is a grid map on which the 3D terrain data is combined with the battle field data, and each grid node on the map has UGV's survival probability value. The suggested path planning algorithm finds the optimal path by comparing the survival probability value of the grid nodes. At last, the simulation program has been developed, and the results are shown to verify the suggested algorithm.","PeriodicalId":431699,"journal":{"name":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"UGV optimal path planning algorithm by using 3D survivability map\",\"authors\":\"Min-Ho Kim, Min-Cheol Lee\",\"doi\":\"10.1109/URAI.2013.6677377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"UGV has widely used in the battlefield, thus UGV's survivability technique has become one of the main issue on the path planning algorithm. In this study, 3D survivability map is suggested for UGV survivability, and the optimal path planning algorithm on this map is also suggested. 3D survivability map is a grid map on which the 3D terrain data is combined with the battle field data, and each grid node on the map has UGV's survival probability value. The suggested path planning algorithm finds the optimal path by comparing the survival probability value of the grid nodes. At last, the simulation program has been developed, and the results are shown to verify the suggested algorithm.\",\"PeriodicalId\":431699,\"journal\":{\"name\":\"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URAI.2013.6677377\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2013.6677377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
UGV optimal path planning algorithm by using 3D survivability map
UGV has widely used in the battlefield, thus UGV's survivability technique has become one of the main issue on the path planning algorithm. In this study, 3D survivability map is suggested for UGV survivability, and the optimal path planning algorithm on this map is also suggested. 3D survivability map is a grid map on which the 3D terrain data is combined with the battle field data, and each grid node on the map has UGV's survival probability value. The suggested path planning algorithm finds the optimal path by comparing the survival probability value of the grid nodes. At last, the simulation program has been developed, and the results are shown to verify the suggested algorithm.