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Using personnel movements for indoor autonomous environment discovery

We present a novel method of extracting topological and metric geographical data using only positional data sensed from personnel movements. We extend research from the field of robotics to cope with the gross nonuniformity of sightings that is characteristic of real people in an indoor environment, and any unintentional obstruction of positioning by the user. We use real data collected using the Bat positioning system installed in the Laboratory for Communication Engineering to present the results of implementing the method. We successfully derive useful information from the data, and suggest further ways in which the techniques described are useful in a ubiquitous, sensor-driven computing environment.