Improving Gas Tomography with Mobile Robots: An Evaluation of Sensing Geometries in Complex Environments

被引：0

作者：

Arain, Muhammad Asif ^{[1
]}

Fan, Han ^{[1
]}

Bennetts, Victor Hernandez ^{[1
]}

Schaffernicht, Erik ^{[1
]}

Lilienthal, Achim J. ^{[1
]}

机构：

[1] Orebro Univ, Ctr Appl Autonomous Sensor Syst AASS, Mobile Robot & Olfact Lab, Orebro, Sweden

来源：

2017 ICOCS/IEEE INTERNATIONAL SYMPOSIUM ON OLFACTION AND ELECTRONIC NOSE (ISOEN 2017) | 2017年

关键词：

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

An accurate model of gas emissions is of high importance in several real-world applications related to monitoring and surveillance. Gas tomography is a non-intrusive optical method to estimate the spatial distribution of gas concentrations using remote sensors. The choice of sensing geometry, which is the arrangement of sensing positions to perform gas tomography, directly affects the reconstruction quality of the obtained gas distribution maps. In this paper, we present an investigation of criteria that allow to determine suitable sensing geometries for gas tomography. We consider an actuated remote gas sensor installed on a mobile robot, and evaluated a large number of sensing configurations. Experiments in complex settings were conducted using a state-of-the-art CFD-based filament gas dispersal simulator. Our quantitative comparison yields preferred sensing geometries for sensor planning, which allows to better reconstruct gas distributions.

引用

页数：3

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