Odor Plume Simulation And Odor Source Localization In Dynamic Airflow Environments

Mobile robot odor source localization (OSL) research, which aims to find one ormultiple previously unknown odor sources using one or multiple mobile robotsequipped with odor concentration and other auxiliary sensors, began from1990s. Thisresearch is related to the fields such as sensing and information processing, mobilerobotics, computation intelligence, hydrodynamics and bionics. It is expected that theOSL research will have a wide application in toxic/harmful gas leak detection, firesource monitor, post-disaster rescue and deep-sea hydrothermal vent exploration.Odor molecules released from their source and diffused in the air form an odorplume. The simulation of the odor plume on the one hand can help to understand theconcentration distribution; on the other hand can be a good auxiliary for the OSLexperiments. Focusing on the mobile robot odor source localization and odor plumesimulation problems, the achievement of this dissertation can be concluded asfollows.The multi-scale analysis method is adopted to study the pulsant characteristics ofsingle-point wind velocities under multiple time scales. In outdoor environments, thedispersion of the odor plume is dominated by the wind. However, the characteristicsof the pulsant wind velocities of different time scales are not clear yet. To address thisproblem, the multi-scale pulsant signals of the wind velocities are derived byempirical mode decomposition method, and the autocorrelation, sample entropy andturbulent energy of these pulsant signals are analysed. The impact of these pulsantsignals on wind steadiness is also investigated. Results show that the small-scalepulsant signals are more irregular than the large-scale ones. The pulsant signals underthe time scales from8s to240s are the main causes of the wind direction fluctuation.To study the uniformity of the wind direction in the wind field, the spatialwind-direction consistency index is proposed. The comparison between the spatialwind-direction consistency index and the wind speed shows that the wind direction ismore uniform when there is higher wind speed and vice versa.The dynamic conformity and correlation analysis methods are used to investigatethe relationship of the wind velocities in different locations. Results show that thecorrelation and the similarity of the dynamics properties of the wind velocitysequences recorded at the positions being close to each other and having similar terrain are more significant.In view of the drawbacks of current odor plume simulation models, a real winddata based odor plume simulation environment is built. The simulation wind field isderived using temporal interpolation and spatial interpolation of the real wind fielddata. The modified filament based atmospheric dispersion model is used as the plumemodel. The metal oxide semiconductor gas sensor model is also built. The comparisonof the simulated plume and real plume shows that they have similar instantaneous andstatistical characteristics.A simulated annealing based odor source localization algorithm is put forward.The algorithm obtains the maximum of the concentration field, which is exactly theodor source, employing a simulated-annealing strategy. The simulation on the openoutdoor scene and the experiments in the indoor scene verify that the proposedalgorithm is able to locate the odor source accurately. At the same time, the influencesof wind and concentration fluctuation can be overcome, and the local extrema can beavoided.