Scholarlink

This paper presents a distributed formation algorithm strategy for drones based on artificial potential fields, enabling drones to follow reference points and form formations. This algorithm achieves the drone's following of reference points by introducing bounded potentials and certain controls, while also addressing the issues of drone formation gathering, obstacle avoidance during formation flight, and preventing collisions between drones. In addition, sliding mode control is employed to give the algorithm a certain degree of anti-jamming capability. Both parts of the algorithm utilize the Lyapunov function to prove stability. Finally, simulations of the proposed formation algorithm are conducted to verify its rationality and effectiveness.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Based on Artificial Potential Field Method Drone Anti-jamming Formation Behavior Flight Control Algorithm

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Songsong Ji,
  • Qite Wang,
  • Yuqing He,
  • Tizhou Qiao,
  • Jia Zhao

摘要

This paper presents a distributed formation algorithm strategy for drones based on artificial potential fields, enabling drones to follow reference points and form formations. This algorithm achieves the drone's following of reference points by introducing bounded potentials and certain controls, while also addressing the issues of drone formation gathering, obstacle avoidance during formation flight, and preventing collisions between drones. In addition, sliding mode control is employed to give the algorithm a certain degree of anti-jamming capability. Both parts of the algorithm utilize the Lyapunov function to prove stability. Finally, simulations of the proposed formation algorithm are conducted to verify its rationality and effectiveness.