LE-Nav uses MLLM scene descriptions as conditions for a CVAE that generates planner hyperparameters, achieving navigation performance comparable to human experts in real-world tests.
Long-term navigation for autonomous robots based on spatio-temporal map prediction,
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Learning to Tune Like an Expert: Interpretable and Scene-Aware Navigation via MLLM Reasoning and CVAE-Based Adaptation
LE-Nav uses MLLM scene descriptions as conditions for a CVAE that generates planner hyperparameters, achieving navigation performance comparable to human experts in real-world tests.