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UAV Cluster Mission Planning Strategy for Area Coverage Tasks.

Xiaohong Yan1,2, Renwen Chen1, Zihao Jiang1

  • 1College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.

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|November 25, 2023
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Summary

This study introduces an efficient mission planning strategy for unmanned aerial vehicle (UAV) clusters to optimize area coverage tasks. The proposed method improves task allocation efficiency and energy consumption for UAV swarms.

Keywords:
UAVUAV clusterarea coveragepath planningtask assignment

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Area of Science:

  • Robotics and Automation
  • Artificial Intelligence
  • Aerospace Engineering

Background:

  • Unmanned aerial vehicle (UAV) clusters face challenges in area coverage tasks, including inefficient task distribution and high energy usage.
  • Effective mission planning is crucial for optimizing the performance of multi-UAV systems in complex environments.

Purpose of the Study:

  • To propose an efficient mission planning strategy for UAV clusters to address challenges in area coverage tasks.
  • To enhance task assignment, efficiency, and energy consumption in three-dimensional area coverage operations.

Main Methods:

  • Analysis of area coverage search tasks and determination of coverage schemes.
  • Division of task areas into subareas and a step-by-step solution for UAV cluster task allocation.
  • Application of an improved fuzzy C-clustering algorithm for UAV task area determination.
  • Development of an optimized particle swarm hybrid ant colony (PSOHAC) algorithm for path planning.

Main Results:

  • The proposed strategy ensures full coverage of the task area and efficient task allocation for UAV clusters.
  • Simulation experiments validate the feasibility and superiority of the developed mission planning scheme.
  • The method achieves a maximum improvement of 21.9% in balanced energy consumption efficiency.
  • Overall energy efficiency of the UAV cluster is improved by up to 7.9% compared to existing algorithms.

Conclusions:

  • The developed mission planning strategy effectively addresses challenges in UAV cluster area coverage.
  • The optimized PSOHAC algorithm significantly enhances path planning and energy efficiency.
  • The proposed approach offers a superior solution for efficient and energy-conscious UAV swarm operations.