Thien-Minh Nguyen, T. Nguyen, Muqing Cao, Zhirong Qiu, Lihua Xie
{"title":"Integrated UWB-Vision Approach for Autonomous Docking of UAVs in GPS-denied Environments","authors":"Thien-Minh Nguyen, T. Nguyen, Muqing Cao, Zhirong Qiu, Lihua Xie","doi":"10.1109/ICRA.2019.8793851","DOIUrl":null,"url":null,"abstract":"Though vision-based techniques have become quite popular for autonomous docking of Unmanned Aerial Vehicles (UAVs), due to limited field of view (FOV), the UAV must rely on other methods to detect and approach the target before vision can be used. In this paper we propose a method combining Ultra-wideband (UWB) ranging sensor with vision-based techniques to achieve both autonomous approaching and landing capabilities in GPS-denied environments. In the approaching phase, a robust and efficient recursive least-square optimization algorithm is proposed to estimate the position of the UAV relative to the target by using the distance and relative displacement measurements. Using this estimate, UAV is able to approach the target until the landing pad is detected by an onboard vision system, then UWB measurements and vision-derived poses are fused with onboard sensor of UAV to facilitate an accurate landing maneuver. Real-world experiments are conducted to demonstrate the efficiency of our method.","PeriodicalId":6730,"journal":{"name":"2019 International Conference on Robotics and Automation (ICRA)","volume":"18 1","pages":"9603-9609"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Robotics and Automation (ICRA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRA.2019.8793851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41
Abstract
Though vision-based techniques have become quite popular for autonomous docking of Unmanned Aerial Vehicles (UAVs), due to limited field of view (FOV), the UAV must rely on other methods to detect and approach the target before vision can be used. In this paper we propose a method combining Ultra-wideband (UWB) ranging sensor with vision-based techniques to achieve both autonomous approaching and landing capabilities in GPS-denied environments. In the approaching phase, a robust and efficient recursive least-square optimization algorithm is proposed to estimate the position of the UAV relative to the target by using the distance and relative displacement measurements. Using this estimate, UAV is able to approach the target until the landing pad is detected by an onboard vision system, then UWB measurements and vision-derived poses are fused with onboard sensor of UAV to facilitate an accurate landing maneuver. Real-world experiments are conducted to demonstrate the efficiency of our method.