Heterogeneous map merging using WiFi signals

We propose a map merging algorithm that is capable of merging together heterogeneous maps independently built by different robots. Heterogeneous map merging is a crucially important problem for scenarios where multiple heterogeneous robots collaborate to provide situational awareness in urban search and rescue, patrolling, and explorations tasks, just to name a few. To remedy the lack of uniform representation between heterogeneous map models, we rely on the ubiquitous presence of WiFi signals in today's environments. Our solution consists of three steps. First, the overlap between the heterogeneous maps being merged is determined. Second, metric correspondences between overlapping parts are established. Third, the merging is improved by exploiting the structural properties inherent to graph-based maps. Our proposed system is validated using various occupancy grid and appearance-based maps built in real-world conditions, the results of which confirm its strengths. To the best of our knowledge, this is the first solution to the heterogeneous map merging problem.