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For mobile robots that operate in complex, uncontrolled environments, estimating air flow models can be of great importance. Aerial robots use air flow models to plan optimal navigation paths and to avoid turbulence-ridden areas. Search and rescue platforms use air flow models to infer the location of gas leaks. Environmental monitoring robots enrich pollution distribution maps by integrating the information conveyed by an air flow model. In this paper, we present an air flow modelling algorithm that uses wind data collected at a sparse number of locations to estimate joint probability distributions over wind speed and direction at given query locations. The algorithm uses a novel extrapolation approach that models the air flow as a linear combination of laminar and turbulent components. We evaluated the prediction capabilities of our algorithm with data collected with an aerial robot during several exploration runs. The results show that our algorithm has a high degree of stability with respect to parameter selection while outperforming conventional extrapolation approaches. In addition, we applied our proposed approach in an industrial application, where the characterization of a ventilation system is supported by a ground mobile robot. We compared multiple air flow maps recorded over several months by estimating stability maps using the Kullback-Leibler divergence between the distributions. The results show that, despite local differences, similar air flow patterns prevail over time. Moreover, we corroborated the validity of our results with knowledge from human experts.
Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind
(2022)
This presentation reports the use of the first gas dispersion simulator capable of generating large wind fluctuation, to test a modification to a gas source localization algorithm and study how the change affects it. Gas source localization at an outdoor environment is a challenging task mainly due to the complexity of the spreading gas caused by the unpredictable nature of constantly changing wind. Therefore, a novel use of outdoor wind in developing a gas source localization system by simulation will be shared. To consider the characteristic of sudden but large and unpredictable changes in wind direction, recorded outdoor wind was used to simulate a realistic outdoor gas dispersion which has been done for the first time. With the use of this simulator, a modification to a mobile robot-based gas source localization algorithm was evaluated. Multiple simulations of the modified and the original algorithm were done to study the effect of the tested modification. The results showed that a small difference in the algorithm can greatly impact the results. From this study, we consider the use of simulation consisting of the necessary traits to evaluate outdoor gas source localization, has the potential to accelerate the development of a reliable localization system.
Geogenic gases such as CH4 or CO2 from natural sources, gases (CCS-CO2, H2, Natural
gas, City gas …) from a geological repository, or a leaking gas pipeline can present serious
risks in industrial and urban areas where the density of infrastructural elements increases as
well as above and below ground. To extend the lead time for risk treatment in such critical
regions, reliable detection of gases within the shallow subsurface is required to observe
critical gas accumulations before degassing into the atmosphere.
A near real-time monitoring approach is introduced to determine the volumetric expansion of
such a gas escaping from a leak in the subsurface. Considering the pressure relaxation with
the ambient air pressure, the approach enables the forecasting of the final size of a
pressurized gas body in terms of characteristic lengths. According to theoretical basics, such
a characteristic length, which allows to perform a gas (safety) measurement based on a
purely geometrical measure, behaves independently of subsurface properties, i.e., it enables
a reliable quantification of the escaping gas, irrespective of its heterogeneous flow path
distribution. A field test for a 10 l/min pinhole leakage of CO2 injected in an unsaturated Chernozemic soil (agricultural test field Bad Lauchstädt)that was equipped with linear gas sensors demonstrates the lateral-vertical volumetric gas expansion along the environment of these gas sensors, and confirms the applicability of the new characteristic length approach.
Mobile Robot Olfaction
(2013)