SAGR builds a semantic area graph from occupancy maps so LLMs can assign rooms to robots for language-guided search, staying competitive with standard exploration while improving semantic target finding by up to 18.8% in large environments.
Efficient autonomous exploration planning of large-scale 3-d environments,
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AIMAPP unifies online topological mapping, localisation, and planning under a single active-inference generative model for self-supervised robot navigation.
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Semantic Area Graph Reasoning for Multi-Robot Language-Guided Search
SAGR builds a semantic area graph from occupancy maps so LLMs can assign rooms to robots for language-guided search, staying competitive with standard exploration while improving semantic target finding by up to 18.8% in large environments.
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Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference
AIMAPP unifies online topological mapping, localisation, and planning under a single active-inference generative model for self-supervised robot navigation.