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.
Object goal navigation using goal-oriented semantic exploration
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FSUNav's dual brain-inspired modules achieve state-of-the-art zero-shot goal navigation across heterogeneous robots with improved speed, safety, and generalization.
Introduces a hierarchical VLN architecture with asynchronous layers, incremental memory graph, and WTRP-based exploration that improves success and efficiency on resource-constrained robots.
citing papers explorer
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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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FSUNav: A Cerebrum-Cerebellum Architecture for Fast, Safe, and Universal Zero-Shot Goal-Oriented Navigation
FSUNav's dual brain-inspired modules achieve state-of-the-art zero-shot goal navigation across heterogeneous robots with improved speed, safety, and generalization.
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A Deployable Embodied Vision-Language Navigation System with Hierarchical Cognition and Context-Aware Exploration
Introduces a hierarchical VLN architecture with asynchronous layers, incremental memory graph, and WTRP-based exploration that improves success and efficiency on resource-constrained robots.