A passage-aware structural mapping approach for RGB-D VSLAM detects doors and openings via joint geometric-semantic-topological fusion and adds passage abstractions to vS-Graphs scene graphs.
vs-graphs: Integrating visual slam and situa- tional graphs through multi-level scene understanding
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S-Path uses the metric-semantic structure of indoor 3D scene graphs for two-stage planning with parallel subproblem decomposition and heuristic reuse on replanning, reporting 6x average planning time reduction versus classical sampling-based methods.
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Passage-Aware Structural Mapping for RGB-D Visual SLAM
A passage-aware structural mapping approach for RGB-D VSLAM detects doors and openings via joint geometric-semantic-topological fusion and adds passage abstractions to vS-Graphs scene graphs.
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Situationally-aware Path Planning Exploiting 3D Scene Graphs
S-Path uses the metric-semantic structure of indoor 3D scene graphs for two-stage planning with parallel subproblem decomposition and heuristic reuse on replanning, reporting 6x average planning time reduction versus classical sampling-based methods.