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Research on Real-Time Roundup and Dynamic Allocation Methods for Multi-Dynamic Target Unmanned Aerial Vehicles.

Jinpeng Li1, Ruixuan Wei2, Qirui Zhang2

  • 1Graduate College, Air Force Engineering University, Xi'an 710051, China.

Sensors (Basel, Switzerland)
|October 26, 2024
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Summary

This study introduces a novel algorithm for Unmanned Aerial Vehicle (UAV) swarms to effectively round up multiple, dynamically escaping targets. The new method significantly improves roundup efficiency and success rates in complex environments.

Keywords:
dynamic distributionmulti-targetreal-time roundupunmanned aerial vehicles

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Area of Science:

  • Robotics and Autonomous Systems
  • Artificial Intelligence
  • Control Theory

Background:

  • Encirclement of multiple dynamic targets by Unmanned Aerial Vehicles (UAVs) is challenging due to environmental uncertainties and target evasion tactics.
  • Traditional methods often fail when targets are scattered or employ complex escape strategies, leading to encirclement failures.

Purpose of the Study:

  • To develop a real-time algorithm for the dynamic allocation and roundup of multiple, simultaneously escaping targets using UAVs.
  • To enhance the success rate and efficiency of multi-target encirclement operations in complex, dynamic environments.

Main Methods:

  • An artificial potential field function was adapted to create a real-time dynamic obstacle avoidance model.
  • A linear matching method was employed to establish an optimal allocation strategy for target encirclement.
  • Simulations were conducted with varying numbers of UAVs, obstacles, and target escape behaviors.

Main Results:

  • The proposed algorithm successfully rounded up multiple dynamic targets in simulated scenarios with random initial positions for UAVs and obstacles.
  • Demonstrated a 50% increase in roundup efficiency and a 10-fold improvement in formation success rate.
  • The task UAVs exhibited effective obstacle avoidance capabilities, enabling their integration into other real-time allocation algorithms.

Conclusions:

  • The developed algorithm provides an effective solution for real-time, multi-dynamic target roundup and dynamic allocation using UAV swarms.
  • The system's ability to handle complex scenarios with dynamic targets and obstacles significantly enhances mission success rates.
  • The obstacle-avoiding UAVs can be utilized in broader applications for real-time task allocation and coordination.