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The authors consider the problem of learned navigation of a circular robot R, of radius delta (>or=0), through a terrain whose model is not a priori known. The authors consider two-dimensional finite-sized terrains populated by an unknown (but finite) number of simple polygonal obstacles. The number and locations of the vertices of each obstacle are unknown to R; R is equipped with a sensor system that detects all vertices and edges that are visible from its present location. The authors deal with two problems: the visit problem and the terrain model acquisition problem. In the visit problem, the robot is required to visit a sequence of destination points, and in the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain. The authors present an algorithmic network framework for solving these two problems based on a retraction of the free space onto the Voronoi diagram of the terrain.>
Rao et al. (Tue,) studied this question.