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Geometry vs Structure: Graph-Based Diagnostics for LiDAR Point-Cloud Simulation Fidelity

arXiv · AI, language, vision and robotics · article · Sep 14, 2026 · UTC

Digital twins provide a scalable and cost-effective complement to real-world testing for validating autonomous-driving and advanced driver-assistance system (ADAS) sensor pipelines. However, quantifying their fidelity remains challenging, particularly for 3D LiDAR point clouds, where conventional geometric metrics may overlook important structural discrepancies. We present a graph-based framework for evaluating the structural fidelity of simulated LiDAR point clouds against real-world scans. While scan-level metrics such as Chamfer distance capture point-wise geometric similarity, they do not

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