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SAS: A Semantic Autonomy Framework for VLM-Integrated Indoor Mobile Robots

The paper proposes the Semantic Autonomy Stack (SAS), a six-layer integration framework that builds semantic reasoning, mission interface, and operational memory layers on a validated ROS 2/Nav2 foundation. It uses a deterministic-first cascade that escalates unresolved or guarded cases to a pretrained vision-language model (VLM).

Part of the event: Paper Release: Semantic Autonomy Stack (SAS) Six-Layer Framework

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