Autonomous Landing of a Micro Aerial Vehicle on a Moving Platform Using a Composite Landmark

Abstract

In the existing vision-based autonomous landing systems for micro aerial vehicles (MAVs) on moving platforms, the limited range of landmark localization, the unknown measurement bias of the moving platform (such as wheel-slip or inaccurate calibration of encoders), and landing trajectory knotting seriously affect system performance. To overcome the above shortcomings, an autonomous landing system using a composite landmark is proposed in this paper. In the proposed system, a notched ring landmark and two-dimensional landmark are combined as an R2D landmark to provide visual localization over a wide range. In addition, the wheel-slip and imprecise calibration of encoders are modeled as the unknown measurement bias of the encoders and estimated online via an extended Kalman filter. The landing trajectory is planned by a solver as a convex quadratic programming problem in each control cycle. Meanwhile, an iterative algorithm for adding equality constraints is proposed and used to verify whether the planned trajectory is feasible or not. The simulation and actual landing experiment results verify the following: the visual localization with the R2D landmark has the advantages of wide localization range and high localization accuracy, the pose estimation result of the moving platform with unknown encoder measurement bias is continuous and accurate, and the proposed landing trajectory planning algorithm provides a continuous trajectory for reliable landing.