Virtual evacuation study with 56 participants finds humans prefer robots that proactively use refuge niches to yield space, with a clear hierarchy over freezing or efficiency-focused strategies.
Applied Sciences14(1), 89 (2023)
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The Semantic Autonomy Stack combines a seven-step parametric resolver handling 88% of instructions in under 0.1 ms with VLM escalation and a five-category cross-robot memory system, achieving 100% accuracy and 103,000-fold latency reduction on Raspberry Pi 5 robots with no GPU or training data.
citing papers explorer
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Beyond Collision Avoidance: Multi-Robot Yielding and Spatial Affordance in Emergency Evacuations
Virtual evacuation study with 56 participants finds humans prefer robots that proactively use refuge niches to yield space, with a clear hierarchy over freezing or efficiency-focused strategies.
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A Semantic Autonomy Framework for VLM-Integrated Indoor Mobile Robots: Hybrid Deterministic Reasoning and Cross-Robot Adaptive Memory
The Semantic Autonomy Stack combines a seven-step parametric resolver handling 88% of instructions in under 0.1 ms with VLM escalation and a five-category cross-robot memory system, achieving 100% accuracy and 103,000-fold latency reduction on Raspberry Pi 5 robots with no GPU or training data.