RoboULM is a new human-in-the-loop LLM-based method for systematic uncertainty analysis in self-adaptive robots, backed by a dedicated taxonomy and positively evaluated by 16 practitioners across four industrial use cases.
The vision of autonomic computing.Computer, 36(1):41–50
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Human-in-the-Loop Uncertainty Analysis in Self-Adaptive Robots Using LLMs
RoboULM is a new human-in-the-loop LLM-based method for systematic uncertainty analysis in self-adaptive robots, backed by a dedicated taxonomy and positively evaluated by 16 practitioners across four industrial use cases.