Robust Methods For Robot Localization Under Changing Illumination Conditions Comparison Of Different Filtering Techniques

The use of omnidirectional systems provides us with rich visual information that allows us to create appearance-based dense maps. This map can be composed of several panoramic images taken from different positions in the environment. When the map contains only visual information, it will depend heavily on the conditions of the environment lighting. Therefore we get different visual information depending on the time of day when the map is created, the state of artificial lighting in the environment, or any other circumstance that causes a change in the illumination of the scene. To obtain a robust map against changes in the illumination of the environment we apply different filters on the panoramic images. After that, we use some compression methods that allow us to reduce the amount of information stored. We have conducted a comprehensive experimentation to study which type of filter best adapts to changing lighting conditions.