A unified framework of secure prompting, state memory, and rule-based safety validation improves LLM-driven robot navigation under prompt injection attacks and obstacle-heavy environments, with modest real-robot verification.
A Survey on Deep Learning Tools Dealing with Data Scarcity: Definitions, Challenges, Solutions, Tips, and Applications
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Enhancing Reliability in LLM-Integrated Robotic Systems: A Unified Approach to Security and Safety
A unified framework of secure prompting, state memory, and rule-based safety validation improves LLM-driven robot navigation under prompt injection attacks and obstacle-heavy environments, with modest real-robot verification.