{"title":"基于面板的水深SLAM加权网格划分","authors":"Junwoo Jang, Jinwhan Kim","doi":"10.1109/OCEANSE.2019.8867531","DOIUrl":null,"url":null,"abstract":"Bathymetric navigation enables the long-term operation of autonomous underwater vehicles by reducing navigation drift errors with no need for GPS position fixes. In the case that a bathymetric map is not available, the simultaneous localization and mapping (SLAM) algorithm is required, but this increases computational complexity and memory requirement. Panel-based bathymetric SLAM could considerably reduce the computational burden. However, it may suffers from incorrect update when the vehicle does not belong to the updated panel. This study proposes a new update method, called weighted grid partitioning, which considers the probability distribution of a vehicle's location, and is more effective in terms of the map accuracy, computational burden, and memory usage compared to standard update methods. The feasibility of the proposed algorithm is verified through simulations.","PeriodicalId":375793,"journal":{"name":"OCEANS 2019 - Marseille","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Weighted Grid Partitioning for Panel-Based Bathymetric SLAM\",\"authors\":\"Junwoo Jang, Jinwhan Kim\",\"doi\":\"10.1109/OCEANSE.2019.8867531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bathymetric navigation enables the long-term operation of autonomous underwater vehicles by reducing navigation drift errors with no need for GPS position fixes. In the case that a bathymetric map is not available, the simultaneous localization and mapping (SLAM) algorithm is required, but this increases computational complexity and memory requirement. Panel-based bathymetric SLAM could considerably reduce the computational burden. However, it may suffers from incorrect update when the vehicle does not belong to the updated panel. This study proposes a new update method, called weighted grid partitioning, which considers the probability distribution of a vehicle's location, and is more effective in terms of the map accuracy, computational burden, and memory usage compared to standard update methods. The feasibility of the proposed algorithm is verified through simulations.\",\"PeriodicalId\":375793,\"journal\":{\"name\":\"OCEANS 2019 - Marseille\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OCEANS 2019 - Marseille\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCEANSE.2019.8867531\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"OCEANS 2019 - Marseille","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANSE.2019.8867531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Weighted Grid Partitioning for Panel-Based Bathymetric SLAM
Bathymetric navigation enables the long-term operation of autonomous underwater vehicles by reducing navigation drift errors with no need for GPS position fixes. In the case that a bathymetric map is not available, the simultaneous localization and mapping (SLAM) algorithm is required, but this increases computational complexity and memory requirement. Panel-based bathymetric SLAM could considerably reduce the computational burden. However, it may suffers from incorrect update when the vehicle does not belong to the updated panel. This study proposes a new update method, called weighted grid partitioning, which considers the probability distribution of a vehicle's location, and is more effective in terms of the map accuracy, computational burden, and memory usage compared to standard update methods. The feasibility of the proposed algorithm is verified through simulations.