MemoGuard checks episodic memories before a communication-limited robot reuses them, because a retrieved action can match the current context and still be unsafe (changed topology, too little battery, an unreliable past outcome). The paper calls these memory traps. MemoGuard validates each memory against topology, resource and outcome contracts and calls local LLM reasoning only when validation fails; in a corridor-inspection simulator it cuts battery safety violations by 76.6% against similarity-only reuse and fallback calls by 21.4% against always reasoning.
Relevance
Memory that was right last week can be wrong today, and this treats stale memory as a safety problem. See long-term autonomy, runtime monitoring and robust robotics.
Links
- arXiv · code
- Subfield: Safety and verification, Planning and navigation, Semantic mapping