An exploratory robot has to solve two elemental problem: mapping and path planning. There are commonly used solutions for the mapping, for instance the shortly presented Occupancy Grid Mapping method. Besides this, an exploratory robot has to detect the areas of interest on the map, choose the next measurement position, and plan an optimal path to that.
The path planning methods usually work on a simplified representation of the original map. A commonly used simplification is the grid transformation. The problems with this transformation inspired me to find better solutions. A more precise representation of the map is the polygon-based representation. In my thesis, I present a method for generating this representation from the Occupancy Grid map, and describing the areas of interest in accord with it. I briefly present the current solutions of pathfinding in polygonal domain, and I present a new pathfinding algorithm, the TPA* algorithm, which is able to find the euclidean optimal path on a triangulated, weakly simple polygon.