Optimized flocking of autonomous drones in confined environments

Gábor Vásárhelyi, Csaba Virágh, Gergő Somorjai, T. Nepusz, Agoston E. Eiben, T. Vicsek

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

We address a fundamental issue of collective motion of aerial robots: how to ensure that large flocks of autonomous drones seamlessly navigate in confined spaces. The numerous existing flocking models are rarely tested on actual hardware because they typically neglect some crucial aspects of multirobot systems. Constrained motion and communication capabilities, delays, perturbations, or the presence of barriers should be modeled and treated explicitly because they have large effects on collective behavior during the cooperation of real agents. Handling these issues properly results in additional model complexity and a natural increase in the number of tunable parameters, which calls for appropriate optimization methods to be coupled tightly to model development. In this paper, we propose such a flocking model for real drones incorporating an evolutionary optimization framework with carefully chosen order parameters and fitness functions. We numerically demonstrated that the induced swarm behavior remained stable under realistic conditions for large flock sizes and notably for large velocities. We showed that coherent and realistic collective motion patterns persisted even around perturbing obstacles. Furthermore, we validated our model on real hardware, carrying out field experiments with a self-organized swarm of 30 drones. This is the largest of such aerial outdoor systems without central control reported to date exhibiting flocking with collective collision and object avoidance. The results confirmed the adequacy of our approach. Successfully controlling dozens of quadcopters will enable substantially more efficient task management in various contexts involving drones.

Original languageEnglish
Article numbereaat3536
JournalScience Robotics
Volume3
Issue number20
DOIs
Publication statusPublished - Jul 25 2018

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Flocking
Collective Motion
Flock
Swarm
Hardware
Multi-robot Systems
Field Experiment
Model Complexity
Collective Behavior
Evolutionary Optimization
Antennas
Fitness Function
Model
Order Parameter
Optimization Methods
Collision
Robot
Perturbation
Motion
Drones

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Mechanical Engineering
  • Control and Optimization

Cite this

Optimized flocking of autonomous drones in confined environments. / Vásárhelyi, Gábor; Virágh, Csaba; Somorjai, Gergő; Nepusz, T.; Eiben, Agoston E.; Vicsek, T.

In: Science Robotics, Vol. 3, No. 20, eaat3536, 25.07.2018.

Research output: Contribution to journalArticle

Vásárhelyi, Gábor ; Virágh, Csaba ; Somorjai, Gergő ; Nepusz, T. ; Eiben, Agoston E. ; Vicsek, T. / Optimized flocking of autonomous drones in confined environments. In: Science Robotics. 2018 ; Vol. 3, No. 20.
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