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The achievement of fully distributed self-organized swarm control of unmanned aerial vehicles (UAVs) in realistic environments is a current challenge in the field of UAV research. This paper investigates the problem of self-organized swarm control of UAVs in dense environments. Based on the behavioral characteristics of biological swarms, a distributed self-organizing Reynolds (SOR) swarm model is proposed to improve the environmental adaptability of UAV swarms. In order to evaluate the performance of the SOR swarm in actual deployment, the proposed SOR swarm method is validated in a real indoor environment based on the Nokov motion capture system using five quadrotor UAVs, and the autonomous navigation of the UAV swarm in an obstacle environment, similar to the flocking behavior of a bird, is successfully achieved.

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Self-organized Reynolds Swarms of Unmanned Aerial Vehicles in Dense Environments

  • 会议论文

  • 发表日期：

    2025年

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  • Yaozu Ding,
  • Hui Xiong,
  • Xiuzhi Shi,
  • Jinzhen Liu,
  • Yimei Chen,
  • Jiaxing Wang

摘要

The achievement of fully distributed self-organized swarm control of unmanned aerial vehicles (UAVs) in realistic environments is a current challenge in the field of UAV research. This paper investigates the problem of self-organized swarm control of UAVs in dense environments. Based on the behavioral characteristics of biological swarms, a distributed self-organizing Reynolds (SOR) swarm model is proposed to improve the environmental adaptability of UAV swarms. In order to evaluate the performance of the SOR swarm in actual deployment, the proposed SOR swarm method is validated in a real indoor environment based on the Nokov motion capture system using five quadrotor UAVs, and the autonomous navigation of the UAV swarm in an obstacle environment, similar to the flocking behavior of a bird, is successfully achieved.