Three-Dimensional Statistical Gas Distribution Mapping in an Uncontrolled Indoor Environment

Reggente, Matteo; Lilienthal, Achim J.; Pardo, Matteo; Sberveglieri, Giorgio

doi:10.1063/1.3156484

Cited by 15 publications

(10 citation statements)

References 12 publications

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“…As an extension of the Kernel DM+V algorithm in [4] we present the Kernel DM+V/W algorithm, which uses information about the local airflow in addition to gas sensors measurements to compute a statistical gas distribution model. The kernel extrapolation methods have also been extended recently to scenarios where multiple odor sources are present [10] and to the three-dimensional case [11].…”

Section: Related Workmentioning

confidence: 99%

Using local wind information for gas distribution mapping in outdoor environments with a mobile robot

Reggente

Lilienthal

2009

2009 IEEE Sensors

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Abstract-In this paper we introduce a statistical method to build two-dimensional gas distribution maps (Kernel DM+V/W algorithm). In addition to gas sensor measurements, the proposed method also takes into account wind information by modeling the information content of the gas sensor measurements as a bivariate Gaussian kernel whose shape depends on the measured wind vector. We evaluate the method based on real measurements in an outdoor environment obtained with a mobile robot that was equipped with gas sensors and an ultrasonic anemometer for wind measurements. As a measure of the model quality we compute how well unseen measurements are predicted in terms of the data likelihood. The initial results are encouraging and show a clear improvement of the proposed method compared to the case where wind is not considered.

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Section: Related Workmentioning

confidence: 99%

Using local wind information for gas distribution mapping in outdoor environments with a mobile robot

Reggente

Lilienthal

2009

2009 IEEE Sensors

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“…Recent developments of the "Kernel DM+V" algorithm from Reggente and Lilienthal extend the algorithm to estimate a 3D map [58] and to include in the mapping process information coming from an anemometer placed in proximity of the gas sensors [59]. The wind information is integrated by giving the kernel an elliptical shape and modifying the orientation of the ellipse according to the wind direction.…”

Section: Gas Distribution Mappingmentioning

confidence: 99%

Gas Discrimination for Mobile Robots

Trincavelli

2011

Künstl Intell

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The problem addressed in this thesis is discrimination of gases with an array of partially selective gas sensors. Metal oxide gas sensors are the most common gas sensing technology since they have, compared to other gas sensing technologies, a high sensitivity to the target compounds, a fast response time, they show a good stability of the response over time and they are commercially available. One of the most severe limitation of metal oxide gas sensors is the scarce selectivity, that means that they do not respond only to the compound for which they are optimized but also to other compounds. One way to enhance the selectivity of metal oxide gas sensors is to build an array of sensors with different, and partially overlapping, selectivities and then analyze the response of the array with a pattern recognition algorithm. The concept of an array of partially selective gas sensors used together with a pattern recognition algorithm is known as an electronic nose (e-nose).In this thesis the attention is focused on e-nose applications related mobile robotics. A mobile robot equipped with an e-nose can address tasks like environmental monitoring, search and rescue operations or exploration of hazardous areas. In e-noses mounted on mobile robots the sensing array is most often directly exposed to the environment without the use of a sensing chamber. This choice is often made because of constraints in weight, costs and because the dynamic response obtained by the direct interaction of the sensors with the gas plume contains valuable information. However, this setup introduces additional challenges due to the gas dispersion that characterize natural environments. Turbulent and chaotic gas dispersal causes the array of sensors to be exposed to rapid changes in concentration that cause the sensor response to be highly dynamic and to seldom reach a steady state. Therefore the discrimination of gases has to be performed on features extracted from the dynamics of the signal. The problem is further complicated by variations in temperature and humidity, physical variables to which metal oxide gas sensors are crossensitive. For these reasons the problem of discrimination of gases when an array of sensors is directly exposed to the environment is different from when the array of sensors is in a controlled chamber.i ii This thesis is a compilation of papers whose contributions are two folded. On one side new algorithms for discrimination of gases with an array of sensors directly exposed to the environment are presented. On the other side, innovative experimental setups are proposed. These experimental setups enable the collection of high quality data that allow a better insight in the problem of discrimination of gases with mobile robots equipped with an e-nose. The algorithmic contributions start with the design and validation of a gas discrimination algorithm for gas sensors array directly exposed to the environment. The algorithm is then further developed in order to be able to run online on a robot, thereby enabling t...

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“…8,9 Osório et al 10 proposed the use of multiple gas sensors on a wheeled robot at different heights on a pole to generate a 3D gas distribution map. It is a good first attempt in 3D CPT.…”

Section: Related Workmentioning

confidence: 99%

Chemical plume tracing

Yap

2018

International Journal of Advanced Robotic Systems

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Most of the reported three-dimensional chemical plume tracing methods use stereo sensing method to determine the next tracing step direction. For example, multiple sensors are used for detection in the left, right, up and down directions. Left and right detections are feasible for stereo sniffing; unfortunately, the same approach is infeasible for the up/down sensing of the quadrotor platforms because the propellers of the quadrotor continuously draw the air from the top and bring it down, which affects the sensing of the upper and lower sensors, and fails to determine the subsequent tracing step of up/down direction. Therefore, up/down sensing in the surging stage of chemical plume tracing is ineffective for quadrotor platforms (chemical plume tracing has two stages: surging and casting). To solve the problem, we propose an alternative that is not in the surging but in the casting stage of chemical plume tracing, by designing a new three-dimensional chemical plume tracing technique with variations of altitude (z-axis) control during the casting stage, which has never been considered in the previous works. Besides, we use a computational fluid dynamics software to study the airflow pattern of quadrotor platform. Subsequently, a fuzzy-based stereo-sniffing algorithm is developed by considering the quadrotor propeller's air intake stream angle associated with the environmental wind direction angle, so as to improve the accuracy of stereo sensing. The results of the proposed solutions are verified and validated via both experimental and simulation approaches.

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Three-Dimensional Statistical Gas Distribution Mapping in an Uncontrolled Indoor Environment

Cited by 15 publications

References 12 publications

Using local wind information for gas distribution mapping in outdoor environments with a mobile robot

Using local wind information for gas distribution mapping in outdoor environments with a mobile robot

Gas Discrimination for Mobile Robots

Chemical plume tracing

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