A Distributed Pipeline for Scalable, Deconflicted Formation Flying
Name
2003.01851.pdf
Description
Accepted version
Size
2.78 MB
Format
Adobe PDF
Checksum (MD5)
c9df349e0e0f585de270268441af35a0
Author(s)
Lusk, Parker C
Cai, Xiaoyi
Wadhwania, Samir
Paris, Aleix
Fathian, Kaveh
How, Jonathan P
Date Issued
2020
Journal
IEEE Robotics and Automation Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Author's final manuscript
Abstract
© 2016 IEEE. Reliance on external localization infrastructure and centralized coordination are main limiting factors for formation flying of vehicles in large numbers and in unprepared environments. While solutions using onboard localization address the dependency on external infrastructure, the associated coordination strategies typically lack collision avoidance and scalability. To address these shortcomings, we present a unified pipeline with onboard localization and a distributed, collision-free formation control strategy that scales to a large number of vehicles. Since distributed collision avoidance strategies are known to result in gridlock, we also present a distributed task assignment solution to deconflict vehicles. We experimentally validate our pipeline in simulation and hardware. The results show that our approach for solving the optimization problem associated with formation control gives solutions within seconds in cases where general purpose solvers fail due to high complexity. In addition, our lightweight assignment strategy leads to successful and quicker formation convergence in 96-100% of all trials, whereas indefinite gridlocks occur without it for 33-50% of trials. By enabling large-scale, deconflicted coordination, this pipeline should help pave the way for anytime, anywhere deployment of aerial swarms.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/LRA.2020.3006823
