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simmediumroboticsmetric · varies
Can LLMs Prove Robotic Path Planning Optimality? A Benchmark for Research-Level Algorithm Verification
Description
Robotic path planning problems are often NP-hard, and practical solutions typically rely on approximation algorithms with provable performance guarantees for general cases. While designing such algorithms is challenging, formally proving their approximation optimality is even more demanding, which requires domain-specific geometric insights and multi-step mathematical reasoning over complex operational constraints. Recent Large Language Models (LLMs) have demonstrated strong performance on mathe