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dc.contributor.authorWang, Hao
dc.description.abstractWith the increasing popularity of drones, applications such as exploration, search-and-rescue and autonomous flight have been developed. Many of these applications are based on the drone localization because it is the foundation of navigation and autonomous flight. This project deals with the indoor localization problem of drones and improves the localization accuracy by implementing an integrated localization algorithm. In the domain of indoor localization, there exist many methods such as SLAM (Simultaneous localization and mapping) and UWB (Ultrawide Band). In brief, SLAM is a feature-matching localization and mapping process and UWB is a triangulation localization process based on range measurements. Each method is capable to function as standalone form but both suffer from some flaws. In this project, graph optimization was used to combine both localization methods and the experimental results proved great enhancement in localization accuracy. By using integrated localization methods, this project provided an accurate indoor localization algorithm with an error of less than 10cm. In addition, we have achieved automatic calculation of UWB devices’ coordinates, which facilitates the localization process by automating the manual measurement. This project has successfully increased the localization accuracy in drone applications and proved the effectiveness of sensor fusion and graph optimization. Future works in this topic could focus on further enhancing the localization robustness and system flexibility.en_US
dc.format.extent65 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleIntegration of UWB and SLAM for application in UAVen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorXie Lihuaen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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