Crazyswarm: A large nano-quadcopter swarm. Preiss, J. A., Honig, W., Sukhatme, G. S., & Ayanian, N. In 2017 IEEE International Conference on Robotics and Automation (ICRA), pages 3299–3304, May, 2017. ISSN: nulldoi abstract bibtex We define a system architecture for a large swarm of miniature quadcopters flying in dense formation indoors. The large number of small vehicles motivates novel design choices for state estimation and communication. For state estimation, we develop a method to reliably track many small rigid bodies with identical motion-capture marker arrangements. Our communication infrastructure uses compressed one-way data flow and supports a large number of vehicles per radio. We achieve reliable flight with accurate tracking (\textless; 2 cm mean position error) by implementing the majority of computation onboard, including sensor fusion, control, and some trajectory planning. We provide various examples and empirically determine latency and tracking performance for swarms with up to 49 vehicles.
@inproceedings{preiss_crazyswarm_2017,
title = {Crazyswarm: {A} large nano-quadcopter swarm},
shorttitle = {Crazyswarm},
doi = {10.1109/ICRA.2017.7989376},
abstract = {We define a system architecture for a large swarm of miniature quadcopters flying in dense formation indoors. The large number of small vehicles motivates novel design choices for state estimation and communication. For state estimation, we develop a method to reliably track many small rigid bodies with identical motion-capture marker arrangements. Our communication infrastructure uses compressed one-way data flow and supports a large number of vehicles per radio. We achieve reliable flight with accurate tracking ({\textless}; 2 cm mean position error) by implementing the majority of computation onboard, including sensor fusion, control, and some trajectory planning. We provide various examples and empirically determine latency and tracking performance for swarms with up to 49 vehicles.},
booktitle = {2017 {IEEE} {International} {Conference} on {Robotics} and {Automation} ({ICRA})},
author = {Preiss, James A. and Honig, Wolfgang and Sukhatme, Gaurav S. and Ayanian, Nora},
month = may,
year = {2017},
note = {ISSN: null},
keywords = {Base stations, Crazyswarm, Iterative closest point algorithm, Planning, State estimation, Three-dimensional displays, Tracking, Trajectory, compressed one-way data flow, dense formation indoors, helicopters, miniature quadcopters, motion-capture marker arrangements, nano-quadcopter swarm, sensor fusion, state estimation, system architecture, trajectory optimisation (aerospace), trajectory planning},
pages = {3299--3304}
}
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