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Radioactive sources search method based on multi-robot and Voronoi partition.

Dong Yan1, Yufeng Xiao1, Shizun Sheng1

  • 1Special Environment Robot Technology Laboratory, School of Information Engineering, Southwest University of Science and Technology, Mianyang, 621010, China.

Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine
|August 21, 2024
PubMed
Summary

This study introduces a novel method for locating multiple radioactive sources efficiently using particle filtering and Voronoi partitioning. The approach enhances search accuracy and speed within a defined time frame.

Keywords:
Multi-robotParticle filteringRadioactive source localizationVoronoi partition

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Area of Science:

  • Robotics
  • Environmental Science
  • Signal Processing

Background:

  • Locating unknown radioactive sources is crucial for environmental monitoring and safety.
  • Existing methods may face challenges in efficiency and accuracy when dealing with multiple sources.
  • Coordinated multi-robot systems offer potential for enhanced search capabilities.

Purpose of the Study:

  • To develop and validate a time-efficient method for locating multiple unknown radioactive sources.
  • To leverage particle filtering and Voronoi partitioning for coordinated multi-robot source detection.
  • To demonstrate the accuracy and efficiency of the proposed search strategy.

Main Methods:

  • Area partitioning using Voronoi diagrams with robots as centroids.
  • Concurrent radioactive source search employing particle filtering algorithms.
  • Iterative search process until source termination, ensuring comprehensive coverage.
  • Experimental validation of the proposed multi-robot search methodology.

Main Results:

  • The proposed method successfully located multiple unknown radioactive sources.
  • Experimental results demonstrated high efficiency in terms of time constraints.
  • The accuracy of source localization was validated through conducted experiments.
  • The Voronoi partitioning ensured systematic and non-overlapping search patterns.

Conclusions:

  • The integrated approach of particle filtering and Voronoi partitioning is effective for multi-robot radioactive source localization.
  • This method offers a significant improvement in search efficiency and accuracy compared to traditional approaches.
  • The study provides a robust framework for real-world applications in hazardous environment monitoring.