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

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.