Docking Multirotors in Close Proximity using Learnt Downwash Models

Ajay Shankar, Heedo Woo, Amanda Prorok
11/23/2023
cs.ROcs.LGeess.SY

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Abstract

Unmodeled aerodynamic disturbances pose a key challenge for multirotor flight when multiple vehicles are in close proximity to each other. However, certain missions \textit{require} two multirotors to approach each other within 1-2 body-lengths of each other and hold formation -- we consider one such practical instance: vertically docking two multirotors in the air. In this leader-follower setting, the follower experiences significant downwash interference from the leader in its final docking stages. To compensate for this, we employ a learnt downwash model online within an optimal feedback controller to accurately track a docking maneuver and then hold formation. Through real-world flights with different maneuvers, we demonstrate that this compensation is crucial for reducing the large vertical separation otherwise required by conventional/naive approaches. Our evaluations show a tracking error of less than 0.06m for the follower (a 3-4x reduction) when approaching vertically within two body-lengths of the leader. Finally, we deploy the complete system to effect a successful physical docking between two airborne multirotors in a single smooth planned trajectory.

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@article{shankar2023docking,
  title  = {Docking Multirotors in Close Proximity using Learnt Downwash Models},
  author = {Ajay Shankar and Heedo Woo and Amanda Prorok},
  year   = {2023},
  eprint = {2311.13988},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2311.13988v1}
}

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