Four-rotor UAV navigation algorithms based on stereo visual-intertial SLAM

In the case of too fast movement and lack of features, the simultaneous localization and mapping (SLAM) system based on visual features has low accuracy and is liable to fail in tracking.For this problem, a tightly coupled stereo visual-inertial SLAM (VI-SLAM) algorithm using nonlinear optimization is proposed.Firstly, with the pose of the key frame as the constraint, the bias of the Inertial Measurement Unit (IMU) is initialized.and the pose of the current frame is predicted based on the IMU pre-integration.then, the non-linear local smoothing method is used in the back end optimization, fusing the pose estimation of vision SLAM and IMU pre-integration.and the cumulative error is eliminated by loop detection, the global map optimization is carried out by graph optimization.The performance of the system is validated by EuRoC dataset, and the average accuracy of the system is about twice as high as that of the visual SLAM algorithm.The algorithm is applied to the stereo vision Four-rotor UAV platform, and the practical application of the proposed algorithm is verified.