Gas Distribution Mapping and Gas Source Localisation with a Mobile Robot

This thesis addresses two fundamental problems concerning the application of electrochemical gas sensors on a mobile robot in a real world environment: gas distribution mapping and localisation of a static gas source. Apart from the limitations of current sensor technology, the main difficulty for both of these tasks results from the spreading of gases under natural conditions. Diffusion plays only a minor role in the distribution of odourant molecules at room temperature. The dominant transport mechanisms are convection flow and turbulence. As a consequence, the resulting concentration field is patchy and chaotic, and the actual gas source is usually not located at the point of highest concentration. In order to create a map of a gas distribution it is thus required to extract timeconstant properties of the concentration field from a series of sensor readings collected by a mobile robot. In contrast to conventional mapping techniques, where a considerable overlap between single measurements can be assumed, gas sensor measurements provide information about a very small area. The problem of gas distribution mapping is therefore to create a representation of the average concentration field from sparse point samples of the instantaneous distribution with little or no overlap between single measurements. A new algorithm is introduced in this work to create a representation that stores belief about the average relative concentration of a detected gas in a grid structure. The problem of gas source localisation can be broken down into three subtasks: gas finding, source tracing and source declaration. Gas finding – the detection of an increased concentration – amounts to a basic search task and the selection of a suitable threshold value, a problem that is not addressed in this work. The main part of this thesis is rather concerned with the latter two aspects: following the cues determined from the sensed gas distribution towards its origin (source tracing) and establishing that the source has been found (source declaration). In order to avoid limitation to an environment with a strong airflow, the investigated strategies do not rely on information about wind direction and speed. Accordingly, the experiments were carried out in an unventilated indoor environment where previously suggested methods for gas source localisation, which include periods of upwind movement, are not applicable due to the limitations of current anemometers. A straightforward solution for gas source tracing is to follow an instantaneously measured spatial concentration gradient. Such a strategy was realised on a mobile robot by implementing a direct sensor motor coupling in the manner of a Braitenberg