Sensor fusion for UAV localisation - Lim, Hui Yi (Nanyang Technological University, 2021)
Effective sensor fusion has undoubtedly contributed greatly to UAV applications, either on increasing robustness, reducing uncertainty or improving precision of UAV based positioning system. Visual-inertial Odometry (VIO), which uses cameras with Inertial Measurement Unit (IMU), is particularly common for UAV localisation. However, VIO suffers from inherent limitations of long term estimation drift and may have unreliable performance due to limited features in the environment. These limitations can be overcome by fusing Ultra-wideband (UWB) ranging measurements to remove the visual drift and improve the robustness. Therefore, in this work, an integrated positioning system by combining UWB, IMU and camera based on MSCKF using OpenVINS is being proposed to improve the robustness and accuracy of VIO on both position and orientation. Prior to that, integration of IMU and UWB based on EKF has proven the advantages of fusing UWB with IMU in suppressing the position and orientation error during the navigation process. Design of UWB network has also been extensively discussed to demonstrate the effect on UWB network on improving navigational accuracy. Experiments utilise publicly available datasets for evaluation and the experimental results demonstrate that multi-sensor fusion UAV localisation can effectively achieve high-precision pose estimation. Comprehensively, validation of proposed method against VINS-Fusion has also been done to demonstrate its estimation capabilities.