Autonomous navigation of a mobile robot in human-centered environments requires a map that contains not only a geometric model of the environment for path planning, but also information about environmental objects (doors, furniture, office equipment, etc.). Scene graphs provide such a map representation, where nodes correspond to rooms, locations, and objects, and edges encode spatial connectivity or relationships between objects. Most modern scene graph construction methods have high computational complexity, and the graphs they produce are redundant for the purposes of autonomous robot navigation. This paper proposes a method for constructing Compact Scene Graphs (CSG), which is based on the computationally efficient topological mapping method PRISM-TopoMap and the association of semantic objects with locations on the topological map. The resulting scene graph enables route planning to objects via topological map locations and achieves high-precision localization. The proposed method was experimentally evaluated in the Habitat simulation environment. The experimental results demonstrate that the proposed CSG consumes significantly less memory than traditional metric maps and scene graphs, while providing reliable localization on the topological map through association with semantic objects.
DOI: 10.24412/3033-6007-2026-339-37-52
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Muravyev K. F., Romanenko V. I. Building Compact Scene Graphs Based on a Topological Map for Autonomous Navigation of a Mobile Robot // Intelligent transport. 2026;10(3(39)):37-52. https://doi.org/10.24412/3033-6007-2026-339-37-52