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A Distributed Control Approach to Formation Balancing and Maneuvering of Multiple Multirotor UAVs

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Odelga,  M
Project group: Autonomous Robotics & Human-Machine Systems, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83839

Bülthoff,  HH
Project group: Autonomous Robotics & Human-Machine Systems, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Liu, Y., Montenbruck, J., Zelazo, D., Odelga, M., Rajappa, S., Bülthoff, H., et al. (2018). A Distributed Control Approach to Formation Balancing and Maneuvering of Multiple Multirotor UAVs. IEEE Transactions on Robotics, 34(4): 8429104, pp. 870-882. doi:10.1109/TRO.2018.2853606.


Cite as: https://hdl.handle.net/21.11116/0000-0001-FF55-1
Abstract
In this paper, we propose and experimentally verify a distributed formation control algorithm for a group of multirotor unmanned aerial vehicles (UAVs). The algorithm brings the whole group of UAVs simultaneously to a prescribed submanifold that determines the formation shape in an asymptotically stable fashion in two- and three-dimensional environments. The complete distributed control framework is implemented with the combination of a fast model predictive control method executed at 50 Hz on low-power computers onboard multirotor UAVs and validated via a series of hardware-in-the-loop simulations and real-robot experiments. The experiments are configured to study the control performance in various formation cases of arbitrary time-varying (e.g., expanding, shrinking, or moving) shapes. In the actual experiments, up to four multirotors have been implemented to form arbitrary triangular, rectangular, and circular shapes drawn by the operator via a human–robot interaction device. We also carry out hardware-in-the-loop simulations using up to six onboard computers to achieve spherical formations and a formation moving through obstacles.