Visual-based landing system of a multirotor UAV in GNSS denied environment

Visual-based landing systems for multirotor unmanned aerial vehicles (UAVs) have become an active research area in robotics and aviation. The availability of GNSS signals is essential for most commercial UAVs, but unfortunately, these signals can be lost in certain environments or intentionally denied in military operations. Therefore, visual-based landing systems can provide an alternative solution to enable a low-cost system for precisely landing UAVs in GNSS-denied environments. This paper overviews recent research on visual-based landing systems for multirotor UAVs in a highly unfamiliar environment. The paper presents a comprehensive review of various vision-based techniques, such as optical flow, stereo vision, monocular visual odometry, and deep learning-based methods, which have been proposed for the accurate landing of UAVs in GNSS-denied environments. This paper proposes a multi-camera landing aid system based on ArUco markers. Proposed system allows for a precision landing of the UAV with a pre-programmed approach trajectory. The paper also highlights the challenges and limitations of this topic and provides potential directions for future research. This paper aims to provide a valuable resource for researchers, engineers, and practitioners interested in developing visual-based landing systems for multirotor UAVs in GNSS-denied environments.