University of Maryland used Acrome Stewart Platform for vision-based landing of a multirotor UAS on a moving platform replicating a ship-deck. The UAS is a quadrotor designed
and fabricated in-house with an integrated avionics package developed for autonomous vision-based navigation. A
monocular camera is used for detection and pose estimation of a moving platform. The platform replicates ship-deck
motion using six degrees of freedom capable of oscillatory motions upto 10 cm in linear and 30 degrees in angular
amplitude with speeds upto 50 cm/s. Ship-deck motions of progressively increasing intensity were obtained from
ONR and simulated using the moving platform to understand the problems involved in estimation and tracking of
large stochastic motions. Results were verified with an independent Vicon system. The key conclusion is that it is
possible to track a moving ship-deck with vision alone. Indeed vision based ship-deck position estimation was found
to be near perfect with errors of 1-2 cm. Ship-deck tracking shows a phase lag error that increases with increasing
frequency of ship-deck motion. It was found that this error can be decreased by estimating ship-deck’s velocity and
using it as a feedback in tracking controller.

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