SOURCE-LINKED INTELLIGENCE
A Simulation Platform for AUV Fault Recovery: Exploring LLM-Based Diagnostic Strategies
Autonomous underwater vehicles (AUVs) operating beyond reliable communications must recover from failures without human intervention. We investigate an architecture in which conventional deterministic layered control autonomy manages normal operations, while an invokable large language model (LLM) serves as a diagnostic and recovery planner when onboard anomaly detection identifies performance outside expected limits. Because language models are stochastic, rigorous evaluation requires ensemble testing rather than individual demonstrations. We present a closed-loop simulation architecture that
Read original source ↗ Open in workspace
- recordType
- paper
- region
- Global
Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T16:03:13.000Z
- arXiv · Artificial Intelligence · 2026-09-17T16:03:13.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.