Visual navigation using the monte carlo algorithm

In order to be fully autonomous, a mobile robot must possess the skill of finding its location in a particular environment. In other words, while navigating, a mobile robot must be capable of finding its location in a map of the environment (i.e. its pose < x, y, θ >), otherwise the robot will not be able to complete its task. The problem becomes specially challenging if the robot does not possess any external measure of its global position. Naively, the position/orientation of the robot can be determined using odometry sensors or inertial systems. However, these sensors lack of accuracy when used for long periods of time, due to wheel slippage, drifts and other problems. Localization techniques are used instead, in order to find the position of the mobile agent in the space. The great majority of localization methods rely on finding salient characteristics sensed by the robot and relating them with a map of the environment. These salient characteristics of space are usually called landmarks, and constitute the basis that enables the robot to deduce its location in a previously built map of the environment. In this paper we present a localization method based on the Monte Carlo algorithm.