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Swarm robotics is a complex domain within multi-robot systems that encompasses formation control, movement control, and inter-UAV communication. Coordinates task execution requires effective swarm control, which relies on robust motion control algorithms and reliable data exchange mechanisms. In this work, we propose an operator-leader-followers approach for managing UAV swarms. It comprises the following components: centralized swarm control utilizing the Fixed Global Difference (FGD) algorithm for maintaining inter-UAV distances and facilitating communication; a follow-mode mechanism enabling followers to accurately track leader’s motion; and a point-by-point swarm flight path control system enhancing overall control accuracy. Implemented in the Robot Operating System (ROS) and validated in the Gazebo simulator, the algorithm’s performance is evaluated via the following simulation scenarios: \(\varGamma \) -shape, parabolic, and circular flight paths. The paper discusses experimental results in virtual environments of the Gazebo simulator and demonstrates achieved precision in terms of absolute error and root mean square error (RMSE).

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UAV Swarm Control with Operator-Leader-Followers Approach

  • 会议论文

  • 发表日期：

    2026年

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  • Anna Vaschenko,
  • Oleg Frolov,
  • Ramil Safin,
  • Tatyana Tsoy,
  • Edgar A. Martinez-Garcia,
  • Evgeni Magid

摘要

Swarm robotics is a complex domain within multi-robot systems that encompasses formation control, movement control, and inter-UAV communication. Coordinates task execution requires effective swarm control, which relies on robust motion control algorithms and reliable data exchange mechanisms. In this work, we propose an operator-leader-followers approach for managing UAV swarms. It comprises the following components: centralized swarm control utilizing the Fixed Global Difference (FGD) algorithm for maintaining inter-UAV distances and facilitating communication; a follow-mode mechanism enabling followers to accurately track leader’s motion; and a point-by-point swarm flight path control system enhancing overall control accuracy. Implemented in the Robot Operating System (ROS) and validated in the Gazebo simulator, the algorithm’s performance is evaluated via the following simulation scenarios: \(\varGamma \) -shape, parabolic, and circular flight paths. The paper discusses experimental results in virtual environments of the Gazebo simulator and demonstrates achieved precision in terms of absolute error and root mean square error (RMSE).