Gas Source Localization in Unknown Indoor Environments Using Dual-Mode Information-Theoretic Search

This letter proposes a dual-mode planner for localizing gas sources using a mobile sensor in unknown indoor spaces. The complexity of indoor environments creates constraints on search paths, leading to situations where no valid paths can be generated, which are termed as dead end in this letter. The...

Full description

Saved in:
Bibliographic Details
Published in:IEEE robotics and automation letters 2025-01, Vol.10 (1), p.588-595
Main Authors: Kim, Seunghwan, Seo, Jaemin, Jang, Hongro, Kim, Changseung, Kim, Murim, Pyo, Juhyun, Oh, Hyondong
Format: Article
Language:English
Subjects:
Analytical models
Atmospheric modeling
Dispersion
Environment monitoring and management
Gas detectors
gas source localization
Indoor environment
Mutual information
planning under uncertainty
Position measurement
Robot sensing systems
robotics in hazardous fields
Sensors
Uncertainty
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This letter proposes a dual-mode planner for localizing gas sources using a mobile sensor in unknown indoor spaces. The complexity of indoor environments creates constraints on search paths, leading to situations where no valid paths can be generated, which are termed as dead end in this letter. The proposed dual-mode planner is designed to effectively address the dead end problem while maintaining efficient search paths. In addition, the absence of analytical dispersion models that can be used in unknown indoor environments presents another critical issue for indoor gas source localization (GSL). To address this, we present an indoor Gaussian dispersion model (IGDM) that can analytically model indoor gas dispersion without a complete map. Finally, we establish a GSL framework for indoor environments along with real-time mapping, utilizing the dual-mode planner and IGDM. This framework is validated in indoor scenarios with the realistic gas dispersion simulator. The simulation results show the high success rate of the proposed method, its ability to reduce search time, and its computational efficiency. Furthermore, through real-world experiments, we demonstrate the potential of the proposed approach as a practical solution, evidenced by its satisfactory performance.
ISSN:2377-3766
DOI:10.1109/LRA.2024.3511375