Metrics vs Surveys: An Analysis for Human-Aligned Benchmarking in Social Robot Navigation

Social, also called human-aware, navigation is a key challenge for integrating mobile robots into human environments. The evaluation of such systems is complex, as factors such as comfort, safety, and legibility must be considered. Human-centered assessments, typically conducted through surveys, provide reliable insights but are costly, resourceintensive, and difficult to reproduce or compare across systems. Alternatively, numerical social navigation metrics are easy to compute and facilitate comparisons, yet the community lacks consensus on a standard set of metrics. This work explores the relationship between numerical metrics and human-centered evaluations to identify potential correlations. If specific quantitative measures align with human perceptions, they could serve as preliminary benchmarking tools, providing a human-aligned assessment when large-scale surveys are not feasible. Our results indicate that while current metrics capture some aspects of robot navigation behavior, important subjective factors remain insufficiently represented, necessitating new metrics.