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Coverage path planning for spraying drones.

E Viridiana Vazquez-Carmona1, Juan Irving Vasquez-Gomez1, Juan Carlos Herrera-Lozada1

  • 1Centro de Innovación y Desarrollo Tecnológico en Cómputo (CIDETEC), Instituto Politécnico Nacional (IPN), Av. Luis Enrique Erro S/N, Ciudad de México, 07738, Mexico.

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Summary
This summary is machine-generated.

This study introduces a novel drone path planning method for efficient area disinfection. The approach improves coverage accuracy by modeling spray dispersion and restricting flight to target zones, enhancing smart city sanitation efforts.

Keywords:
COVID-19CoverageDronePath planningSmart citiesSpraying

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Area of Science:

  • Robotics
  • Urban Planning
  • Environmental Science

Background:

  • The COVID-19 pandemic highlights the need for effective public area disinfection.
  • Automated disinfection solutions are crucial for future smart cities.
  • Existing drone path planning methods are not optimized for spray coverage.

Purpose of the Study:

  • To develop an advanced coverage path planning method for spraying drones.
  • To address limitations of current methods regarding spray dispersion and flight boundaries.
  • To enhance the efficiency and effectiveness of automated disinfection operations.

Main Methods:

  • A new sprayer/sprinkler model was developed to realistically represent liquid dispersion.
  • A path planning algorithm was designed to confine drone flight within the target region.
  • The algorithm was tested in simulated environments to evaluate performance.

Main Results:

  • The proposed method demonstrated superior area coverage compared to existing approaches.
  • The sprayer model accurately reflects real-world liquid dispersion patterns.
  • The planning method effectively prevents collisions in confined spaces.

Conclusions:

  • The developed path planning method significantly improves drone-based disinfection efficiency.
  • This technology can be applied to various applications beyond disinfection, such as painting and precision agriculture.
  • The research contributes to the advancement of autonomous systems for urban sanitation and other industries.