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Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment.

Branko Ristic1, Daniel Angley2, Bill Moran3

  • 1School of Engineering, RMIT University, Melbourne, VIC 3000, Australia. branko.ristic@rmit.edu.au.

Sensors (Basel, Switzerland)
|April 22, 2017
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Summary

This study introduces a novel search algorithm for locating toxic substance releases in turbulent environments. The algorithm enhances national security by efficiently identifying release sources using autonomous robots and Bayesian estimation.

Keywords:
biochemical source localisationcognitive searchmobile robots

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Area of Science:

  • Robotics
  • Environmental Science
  • National Security

Background:

  • Accidental or deliberate atmospheric releases of toxic substances pose significant national security risks.
  • Effective source identification is crucial for mitigating the impact of such events.

Purpose of the Study:

  • To develop and analyze a cognitive (infotaxi) search algorithm for locating atmospheric toxic substance release sources.
  • To improve the efficiency and accuracy of source detection in turbulent environments.

Main Methods:

  • Utilizes Bayesian estimation with the Rao-Blackwell dimension-reduction method for source parameter estimation.
  • Employs autonomous robot control in a scalable formation with a centralized replicated fusion architecture.
  • Assumes all-to-all communication for coordinated robot behavior.

Main Results:

  • The proposed algorithm demonstrates effective source localization in turbulent environments.
  • Comprehensive numerical analysis provides statistics on search time and displacement, validating the algorithm's performance.
  • The system integrates estimation and control for autonomous operation.

Conclusions:

  • The developed infotaxi algorithm offers a robust solution for atmospheric toxic release source identification.
  • The approach enhances national security by providing a reliable method for rapid and accurate source detection.
  • Autonomous robot swarms combined with advanced estimation techniques show promise for environmental monitoring and security applications.