Commonly, learning-based topological navigation approaches produce a local policy while preserving some loose connectivity of the space through map. Nevertheless, spurious or missing edges in graph often lead to failure. In this work, we propose sampling-based building method, which results sparser graphs yet with higher performance compared baseline methods. We also maintenance strategies that...