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Exploration and Gas Source Localization in Advection-Diffusion Processes with Potential-Field-Controlled Robotic

Patrick Hinsen1, Thomas Wiedemann1, Dmitriy Shutin1

  • 1Institute of Communications and Navigation, German Aerospace Center (DLR), 82234 Wessling, Germany.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
Summary
This summary is machine-generated.

Mobile robots efficiently locate gas leaks using advanced dispersion models. Even with wind fluctuations, swarms quickly identify sources, demonstrating robust performance in dynamic environments.

Keywords:
advection–diffusion equationartificial potential field controlgas explorationgas source localizationrobotic explorationswarm roboticsuncertainty mapping

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Area of Science:

  • Robotics
  • Environmental Monitoring
  • Control Systems

Background:

  • Mobile multi-robot systems are ideal for hazardous environments, offering redundancy and scalability.
  • Autonomous operation is crucial for efficient swarm exploration and gas source localization.
  • Accurate gas source localization requires robots to sample informative locations based on domain knowledge.

Purpose of the Study:

  • To enhance gas source localization in dynamic environments by incorporating advection and gas concentration field dynamics into the dispersion model.
  • To develop and evaluate a robust exploration strategy for mobile multi-robot systems in challenging conditions.
  • To assess the impact of environmental factors, such as wind fluctuations, on the efficiency of gas leak localization.

Main Methods:

  • Utilized partial differential equations to create a probabilistic gas dispersion model and spatial uncertainty map.
  • Integrated advection and gas concentration field dynamics for a more realistic dispersion model.
  • Employed a potential-field-control approach for robot navigation based on the uncertainty map.

Main Results:

  • The proposed approach robustly recovers gas source distributions, even with wind direction fluctuations.
  • The system can identify potential gas sources within seconds, outperforming previous methods.
  • Larger robot swarms demonstrated faster reduction in localization uncertainty.
  • The approach competes effectively with systematic sampling strategies.

Conclusions:

  • Mobile multi-robot systems are highly applicable and robust for gas source localization in dynamic, challenging environments.
  • Incorporating realistic gas dispersion models, including advection, improves localization accuracy.
  • Swarm size positively impacts the speed of uncertainty reduction and localization efficiency.