Automatic Landing Assist System Using IMU+PnP for Robust Positioning of Fixed-Wing UAVs

This research proposes using a robust Perspective-n-Point (PnP) solution for an automatic landing assistant system for landing a fixed-wing, unmanned, aerial vehicle (UAV) on a runway. Specifically, we attack the problems of: 1) the difficulty in localizing markers on the ground; and 2) multiple candidate poses from PnP algorithms. The former issue can be resolved based on a least-square-based calibration between the camera and the inertial moment unit (IMU) plus geometrical information with consideration given to Lie’s algebra: SO(3). The latter issue has been presented during a long history in the pose estimation field. For an aerial vehicle that can freely move, we propose to resolve this problem using a fusion algorithm between the IMU and PnP, based on object space collinearity. We experiment and analyze that this fusion solution is among the best methods to enhance runway positioning accuracy. Furthermore, discussion based on availability of equipment is presented.

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