Semantic indoor maps

Abstract

The cumbersome process of construction and incremental update of large indoor maps can be simplified by semantic maps. A novel semantic mapping method for indoor environments is proposed which employs a flash-n-extend strategy for constructing and updating the map. At the exposure of every flash event, a 3D snapshot of the environment is taken which is extended until flash event reoccurs. A flash event occurs at a motion state transition of a mobile robot which is detected by the decomposition of motion estimates. The proposed method is evaluated on a set of image sequences and is found to be robust in building indoor maps which are suitable for robust autonomous navigation. The constructed maps provide simplistic representation of the environment which makes it ideal for high-level reasoning tasks.