Graph-based Global Robot Simultaneous Localization and Mapping using Architectural Plans

In this paper, we propose a solution for graph-based global robot
simultaneous localization and mapping (SLAM) using architectural plans. Before
the start of the robot operation, the previously available architectural plan
of the building is converted into our proposed architectural graph (A-Graph).
When the robot starts its operation, it uses its onboard LIDAR and odometry to
carry out an online SLAM relying on our situational graph (S-Graph), which
includes both, a representation of the environment with multiple levels of
abstractions, such as walls or rooms, and their relationships, as well as the
robot poses with their associated keyframes. Our novel graph-to-graph matching
method is used to relate the aforementioned S-Graph and A-Graph, which are
aligned and merged, resulting in our novel informed Situational Graph
(iS-Graph). Our iS-Graph not only provides graph-based global robot
localization, but it extends the graph-based SLAM capabilities of the S-Graph
by incorporating into it the prior knowledge of the environment existing in the
architectural plan