Segment-based robotic mapping in dynamic environments

This paper introduces a dynamic mapping algorithm based on line segments. The use of higher level geometric features allows for fast and robust identification of inconsistencies between incoming sensor data and an existing robotic map. Handling of these inconsistencies using a partial-segment likelihood measure produces a system for robot mapping that evolves with the changing features of a dynamic environment. The algorithm is tested in a large scale simulation of a storage logistics center, a real world office environment, and compared against the current state of the art.