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A Static Area Coverage Algorithm for Heterogeneous AUV Group Based on Biological Competition Mechanism.

Xuan Guo1, Yuepeng Chen1, Dongming Zhao1

  • 1School of Automation, Wuhan University of Technology, Wuhan, China.

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|May 2, 2022
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Summary

This study introduces a new algorithm for heterogeneous autonomous underwater vehicle (AUV) groups to achieve balanced area coverage. The biological competition mechanism (BCM) optimizes resource use better than traditional methods.

Keywords:
Voronoi diagrambiological competition mechanismcentroidal Voronoi tessellation algorithmheterogeneous autonomous underwater vehicle groupload balancing

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Environmental Monitoring

Background:

  • Static area coverage using heterogeneous autonomous underwater vehicle (AUV) groups is crucial in various applications.
  • The centroidal Voronoi tessellation (CVT) algorithm is a common approach but fails to account for AUV heterogeneity, leading to resource inefficiency.

Purpose of the Study:

  • To develop a novel coverage control optimization algorithm for heterogeneous AUV groups.
  • To address the limitations of existing methods by considering individual AUV capabilities and task requirements.

Main Methods:

  • A biological competition mechanism (BCM) is proposed to distribute task loads consistently among heterogeneous AUVs.
  • The algorithm's consistency is rigorously proven using Lyapunov stability theory.

Main Results:

  • Simulations show the BCM algorithm achieves a near-balanced location distribution for heterogeneous AUV groups.
  • The proposed BCM algorithm demonstrates superior performance compared to the CVT algorithm in static area coverage tasks.

Conclusions:

  • The BCM algorithm effectively manages heterogeneous AUV groups for efficient static area coverage.
  • This approach optimizes resource allocation and improves overall mission performance.