FW-ORB-SLAM: A Monocular Visual SLAM Algorithm for Flapping-Wing Flying Robots

Abstract

Visual simultaneous localization and mapping (SLAM) is of great significance for flapping-wing flying robots (FWFRs) to enhance their autonomous navigation capabilities in complex environments. However,during the motion of FWFRs, there are intense image vibrations accompanied by significant illumination changes, which would prevent existing visual SLAM algorithms from being directly applied to FWFRs. Therefore, this paper proposes a modified ORB-SLAM3 algorithm called FW-ORB-SLAM for FWFRs. First, we adopt the fast Fourier transform (FFT) method to map the original images to the frequency domain. Then, based on the characteristic flapping motion of the FWFR, we decompose the frequency domain jitter to obtain stabilized images. Moreover, to mitigate the impact of illumination variations on feature point tracking during outdoor flight, a local adaptive contrast enhancement method is proposed, which enhances the stability of feature point tracking and augments the robustness of the SLAM algorithm. Finally, flight experiments carried out using our self-developed FWFR named U-Dove demonstrate that FW-ORB-SLAM outperforms the state-of-the-art ORB-SLAM3 algorithm, which provides insights into performing vision-based SLAM tasks for the FWFR.