The problem of robot navigation is a fundamental problem for every mobile robot: How to make a robot travel from point A to point B on a given map with maximal efficiency. Solving the problem of robot navigation can be trivial if the robot has means to determine its position in the world at any time by using, for example, reliable sensors. However, in some cases localization means are nonexistent (for example the use of a GPS in indoor environments) or costly (for example the use of laser sensors). In these cases, the problem of robot navigation becomes far more complicated, even when a map is given. The main objective of this paper is to determine a quantitative measure for determining the possibility of navigating in indoor environments given a map for a robot without perfect localization, and to find a navigation path that maximizes the chances of arriving at the destination point safely.