Jiangtao Wang, Yang Zhou, Baihua Li, Q. Meng, Emanuele Rocco, Andrea Saiani
{"title":"水下环境模拟是否有助于自主系统的视觉任务?","authors":"Jiangtao Wang, Yang Zhou, Baihua Li, Q. Meng, Emanuele Rocco, Andrea Saiani","doi":"10.31256/UKRAS19.26","DOIUrl":null,"url":null,"abstract":"To simulate the underwater environment and test\nalgorithms for autonomous underwater vehicles, we developed\nan underwater simulation environment with the Unreal Engine 4\nto generate underwater visual data such as seagrass and\nlandscape. We then used such data from the Unreal environment\nto train and verify an underwater image segmentation model,\nwhich is an important technology to later achieve visual based\nnavigation. The simulation environment shows the potentials for\ndataset generalization and testing robot vision algorithms.","PeriodicalId":424229,"journal":{"name":"UK-RAS19 Conference: \"Embedded Intelligence: Enabling and Supporting RAS Technologies\" Proceedings","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can underwater environment simulation contribute to vision tasks for autonomous systems?\",\"authors\":\"Jiangtao Wang, Yang Zhou, Baihua Li, Q. Meng, Emanuele Rocco, Andrea Saiani\",\"doi\":\"10.31256/UKRAS19.26\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To simulate the underwater environment and test\\nalgorithms for autonomous underwater vehicles, we developed\\nan underwater simulation environment with the Unreal Engine 4\\nto generate underwater visual data such as seagrass and\\nlandscape. We then used such data from the Unreal environment\\nto train and verify an underwater image segmentation model,\\nwhich is an important technology to later achieve visual based\\nnavigation. The simulation environment shows the potentials for\\ndataset generalization and testing robot vision algorithms.\",\"PeriodicalId\":424229,\"journal\":{\"name\":\"UK-RAS19 Conference: \\\"Embedded Intelligence: Enabling and Supporting RAS Technologies\\\" Proceedings\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"UK-RAS19 Conference: \\\"Embedded Intelligence: Enabling and Supporting RAS Technologies\\\" Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31256/UKRAS19.26\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"UK-RAS19 Conference: \"Embedded Intelligence: Enabling and Supporting RAS Technologies\" Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31256/UKRAS19.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Can underwater environment simulation contribute to vision tasks for autonomous systems?
To simulate the underwater environment and test
algorithms for autonomous underwater vehicles, we developed
an underwater simulation environment with the Unreal Engine 4
to generate underwater visual data such as seagrass and
landscape. We then used such data from the Unreal environment
to train and verify an underwater image segmentation model,
which is an important technology to later achieve visual based
navigation. The simulation environment shows the potentials for
dataset generalization and testing robot vision algorithms.