A Distributed Pipeline for Scalable, Deconflicted Formation Flying
© 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 ass...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2021
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| Online Access: | https://hdl.handle.net/1721.1/135445 |
| _version_ | 1826213905460887552 |
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| author | Lusk, Parker C Cai, Xiaoyi Wadhwania, Samir Paris, Aleix Fathian, Kaveh How, Jonathan P |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Lusk, Parker C Cai, Xiaoyi Wadhwania, Samir Paris, Aleix Fathian, Kaveh How, Jonathan P |
| author_sort | Lusk, Parker C |
| collection | MIT |
| description | © 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. |
| first_indexed | 2024-09-23T15:56:42Z |
| format | Article |
| id | mit-1721.1/135445 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:56:42Z |
| publishDate | 2021 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1354452023-01-23T17:24:47Z A Distributed Pipeline for Scalable, Deconflicted Formation Flying Lusk, Parker C Cai, Xiaoyi Wadhwania, Samir Paris, Aleix Fathian, Kaveh How, Jonathan P Massachusetts Institute of Technology. Department of Aeronautics and Astronautics © 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. 2021-10-27T20:23:30Z 2021-10-27T20:23:30Z 2020 2021-04-30T13:55:59Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/135445 en 10.1109/LRA.2020.3006823 IEEE Robotics and Automation Letters Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) arXiv |
| spellingShingle | Lusk, Parker C Cai, Xiaoyi Wadhwania, Samir Paris, Aleix Fathian, Kaveh How, Jonathan P A Distributed Pipeline for Scalable, Deconflicted Formation Flying |
| title | A Distributed Pipeline for Scalable, Deconflicted Formation Flying |
| title_full | A Distributed Pipeline for Scalable, Deconflicted Formation Flying |
| title_fullStr | A Distributed Pipeline for Scalable, Deconflicted Formation Flying |
| title_full_unstemmed | A Distributed Pipeline for Scalable, Deconflicted Formation Flying |
| title_short | A Distributed Pipeline for Scalable, Deconflicted Formation Flying |
| title_sort | distributed pipeline for scalable deconflicted formation flying |
| url | https://hdl.handle.net/1721.1/135445 |
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