Aerial-terrestrial amphibious robots excel in search and rescue tasks in unstructured terrains but face challenges in autonomous navigation indoors. Traditional full-mapping methods can degrade global path planning performance, especially when semi-static obstacles shift, leading to suboptimal paths. We propose a method for constructing building structure grid maps that are unaffected by semistatic obstacles. Our approach includes a building structure recognition algorithm based on an octree structure to differentiate between occupied and free grid cells. Experimental results demonstrate that coverage path planning on building structure grid maps produces superior global paths compared to traditional grid maps, offering a more streamlined and robust solution for autonomous navigation of aerial-terrestrial amphibious robots in indoor environments.