LATIDIA · Robótica

Contiene cascadas de comportamiento de afirmaciones manipuladas en sistemas multi-robot alimentados por LLM

arXiv: 2609.30523v1Tipo de anuncio: nuevo Resumen: los sistemas multirobot con modelo de lenguaje grande (LLM) son vulnerables a la manipulación semántica: un reclamo de estado mundial falso aceptado puede desencadenar una casc de comportamiento en toda la flota

La noticia

arXiv:2609.30523v1 Announce Type: new Abstract: Large language model (LLM)-powered multi-robot systems are vulnerable to semantic manipulation: an accepted false world-state claim can trigger a fleet-wide behavioral cascade, causing unnecessary replanning, increased path costs, congestion, or apparent mission infeasibility. Conditioning on a successful manipulation, we propose an active verification framework that contains its downstream effects before they propagate across the fleet. A dedicated verification module generates a structured Verify-Adapt-Hold plan: selected robots inspect consequential regions, a limited subset provisionally adapts when necessary, and the remaining robots retain their trusted plans. We evaluate the framework in a multi-robot transportation environment using injected false obstacle claims across different impacts and team sizes. Evaluation