Integration of UWB and SLAM for application in UAV
Date of Issue2017
School of Electrical and Electronic Engineering
With 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.
DRNTU::Engineering::Electrical and electronic engineering
Final Year Project (FYP)
Nanyang Technological University