  In this article, we introduce a novel strategy for robotic exploration in
unknown environments using a semantic topometric map. As it will be presented,
the semantic topometric map is generated by segmenting the grid map of the
currently explored parts of the environment into regions, such as
intersections, pathways, dead-ends, and unexplored frontiers, which constitute
the structural semantics of an environment. The proposed exploration strategy
leverages metric information of the frontier, such as distance and angle to the
frontier, similar to existing frameworks, with the key difference being the
additional utilization of structural semantic information, such as properties
of the intersections leading to frontiers. The algorithm for generating
semantic topometric mapping utilized by the proposed method is lightweight,
resulting in the method's online execution being both rapid and computationally
efficient. Moreover, the proposed framework can be applied to both structured
and unstructured indoor and outdoor environments, which enhances the
versatility of the proposed exploration algorithm. We validate our exploration
strategy and demonstrate the utility of structural semantics in exploration in
two complex indoor environments by utilizing a Turtlebot3 as the robotic agent.
Compared to traditional frontier-based methods, our findings indicate that the
proposed approach leads to faster exploration and requires less computation
time.
