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Starling-Behavior-Inspired Flocking Control of Fixed-Wing Unmanned Aerial Vehicle Swarm in Complex Environments with

Weihuan Wu1,2, Xiangyin Zhang1,2, Yang Miao3

  • 1Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.

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Summary

This study introduces a starling-inspired flocking algorithm for unmanned aerial vehicle (UAV) swarms. The novel approach enhances rapid, safe, and collective obstacle avoidance in dynamic 3D environments.

Keywords:
collective motionfixed-wing UAV swarmlocal followingobstacle avoidancestarlings

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Area of Science:

  • Robotics and Control Systems
  • Artificial Intelligence
  • Aerospace Engineering

Background:

  • Large-scale unmanned aerial vehicle (UAV) swarms require robust obstacle avoidance in dynamic, unknown 3D environments.
  • Existing methods often struggle with the speed, safety, and consistency needed for collective navigation.

Purpose of the Study:

  • To develop a bio-inspired flocking control algorithm for enhancing UAV swarm obstacle avoidance.
  • To enable collective, collision-free motion planning for UAVs in complex environments.

Main Methods:

  • A motion model inspired by starling flocking behavior was developed, incorporating collective, evasion, and local-following patterns.
  • These starling-like behavioral patterns were mapped onto a fixed-wing UAV swarm.
  • The algorithm focuses on collective and collision-free motion planning in unknown 3D environments with dynamic obstacles.

Main Results:

  • Simulations demonstrated significant improvements in the speed and order of UAV swarm obstacle avoidance.
  • The proposed algorithm enhanced the safety of the UAV swarm during obstacle avoidance maneuvers.
  • The flocking control algorithm proved effective in dynamic and unknown 3D environments.

Conclusions:

  • The starling-mimicking flocking control algorithm effectively addresses the challenges of large-scale UAV swarm navigation.
  • This bio-inspired approach offers a promising solution for safe and efficient autonomous operation of UAV swarms.