Onboard Controller Design for Nano UAV Swarm in Operator-Guided Collective Behaviors

Tugay Alperen Karaguzel, Victor Retamal, Eliseo Ferrante

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a swarm of Crazyflie nano-drones. The swarm can show various collective behaviors: Flocking, gradient following, going to a chosen point, formation, and scattered search of the environment. The methodology behind the behaviors is executed entirely on-board. Crazyflies use a common radio channel to share positions with each other. If desired, an operator can use the same channel and start, end, change or guide the collective behaviors online during the flight. We use the virtual force vectors and modify the way they are combined to achieve different behaviors instead of developing unique algorithms for each. This allows us to develop more collective behavior types with less effort. In the results, we show a detailed analysis of the behaviors and assess the coordination and the safety of the agents in addition to the performance as a collective. We conclude that our swarm of 6 Crazyflies was successful in the desired behaviors.

Original languageEnglish (US)
Title of host publicationProceedings - ICRA 2023
Subtitle of host publicationIEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3268-3274
Number of pages7
ISBN (Electronic)9798350323658
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Robotics and Automation, ICRA 2023 - London, United Kingdom
Duration: May 29 2023Jun 2 2023

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2023-May
ISSN (Print)1050-4729

Conference

Conference2023 IEEE International Conference on Robotics and Automation, ICRA 2023
Country/TerritoryUnited Kingdom
CityLondon
Period5/29/236/2/23

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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