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A hybrid pipeline for dynamic ontology-based semantic mapping
Semantic mapping plays a crucial role in the ability of a robot to interact with objects, operate and navigate a complex environment. The most common pipeline for semantic mapping consists of geometric mapping and localization (SLAM), perception, semantic fusion and semantic representation. However, more recent works also integrate a form of prior knowledge in their application, most notably knowledge graphs or semantic scene graphs, to improve contextual understanding of the environment. In this paper, we present a hybrid pipeline for semantic mapping. Our system incorporates an external cali
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T14:11:21.000Z
First collected: 2026-09-21T04:51:57.792Z. This is not the publication date.