Hong-Phuoc Nguyen, D. Ngo, Vu-Thanh-Long Duong, Xuan-Tinh Tran
{"title":"Vision-based Navigation for Autonomous Landing System","authors":"Hong-Phuoc Nguyen, D. Ngo, Vu-Thanh-Long Duong, Xuan-Tinh Tran","doi":"10.1109/NICS51282.2020.9335860","DOIUrl":null,"url":null,"abstract":"In this paper, autonomous landing system for unmanned air vehicles (UAVs) based on visual navigation is presented. Two main problems are given with proposed solutions, including autonomous landing system architecture based on Robot Operating System (ROS) and vision algorithm for realtime landing platform detection and pose estimation. Our system was fully implemented on on-board computer and monocular camera equipped on UAVs. Gazebo Simulator with Iris quad-copter model was used for rapidly testing about vision-based and control algorithm. Also, a series of autonomous flight tests are successfully performed for common scenarios with static and moving targets. Obtained results will be verified via normal flight sensors for guaranteeing qualities of our autonomous landing system.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NICS51282.2020.9335860","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, autonomous landing system for unmanned air vehicles (UAVs) based on visual navigation is presented. Two main problems are given with proposed solutions, including autonomous landing system architecture based on Robot Operating System (ROS) and vision algorithm for realtime landing platform detection and pose estimation. Our system was fully implemented on on-board computer and monocular camera equipped on UAVs. Gazebo Simulator with Iris quad-copter model was used for rapidly testing about vision-based and control algorithm. Also, a series of autonomous flight tests are successfully performed for common scenarios with static and moving targets. Obtained results will be verified via normal flight sensors for guaranteeing qualities of our autonomous landing system.