A Visibility‐Based Multitree of a Space Subdivision for Indoor Localization

Abstract

In an era where localization is increasingly vital for daily activities, determining an individual's location and providing suggestions is crucial for successful navigation. Central to our method is the concept of visibility areas, defined as spaces from which a landmark is at least partially visible. We tessellate space into a grid and use raycasting to determine these visibility areas. Visibility areas are further subdivided into sub‐spaces, each representing a unique set of visible landmarks. To efficiently manage and query these sub‐spaces, we create a tree of options for each landmark and merge them into one compact multitree. This structure represents a hierarchical composition of sub‐spaces and enhances query efficiency while storing each sub‐space only once in the memory. The multitree is designed to support the rapid identification of sub‐spaces based on observed landmarks, resulting in efficient localization within the environment is presented to calculating the optimal localization point in a visibility area based on suggested visible landmarks. The paper concludes with a discussion of the approach targeting indoor localization but highlights also its potential for further research and some limitations.