Risk-Aware Semantic Grounding for Trustworthy LLM-Based Robot Planning.

arXiv:2609.37554v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as high-level planners in robot navigation, but their outputs may become unreliable when instructions are ambiguous, unsupported by the environment, or semanti