Flocking algorithm for autonomous flying robots

Csaba Virágh, Gábor Vásárhelyi, Norbert Tarcai, T. Szörényi, Gergó Somorjai, T. Nepusz, T. Vicsek

Research output: Contribution to journalArticle

58 Citations (Scopus)

Abstract

Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks.

Original languageEnglish
Article number025012
JournalBioinspiration and Biomimetics
Volume9
Issue number2
DOIs
Publication statusPublished - 2014

Fingerprint

Robots
Birds
Animals
Decentralized control
Friction
Target tracking
Time delay
Theoretical Models
Animal Models
Communication
Mathematical models
Antennas
Sensors
Experiments

Keywords

  • autonomous navigation
  • collective motion
  • distributed control
  • flying robot flock
  • swarm robotics

ASJC Scopus subject areas

  • Biochemistry
  • Biophysics
  • Biotechnology
  • Molecular Medicine
  • Engineering (miscellaneous)
  • Medicine(all)

Cite this

Flocking algorithm for autonomous flying robots. / Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, T.; Somorjai, Gergó; Nepusz, T.; Vicsek, T.

In: Bioinspiration and Biomimetics, Vol. 9, No. 2, 025012, 2014.

Research output: Contribution to journalArticle

Virágh, Csaba ; Vásárhelyi, Gábor ; Tarcai, Norbert ; Szörényi, T. ; Somorjai, Gergó ; Nepusz, T. ; Vicsek, T. / Flocking algorithm for autonomous flying robots. In: Bioinspiration and Biomimetics. 2014 ; Vol. 9, No. 2.
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