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Barrier-Shaped Recurrent Reinforcement Learning for Autonomous Landing on a Heaving Ship Deck
This paper addresses autonomous landing of unmanned aerial vehicle (UAV) rotorcrafts on a heaving ship deck using a recurrent policy trained via asymmetric actor-critic reinforcement learning: the critic sees 6 s of future deck height during training, while the actor sees only what the onboard senso
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