Metrics vs Surveys: Can Quantitative Measures Replace Human Surveys in Social Robot Navigation? A Correlation Analysis
Trepella, Stefano, Martini, Mauro, Pérez-Higueras, Noé, Ostuni, Andrea, Caballero, Fernando, Merino, Luis, Chiaberge, Marcello
–arXiv.org Artificial Intelligence
Abstract-- Social, also called human-aware, navigation is a key challenge for the integration of 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, resource-intensive, 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 standardized evaluation tools, reducing the dependency on surveys. Our results indicate that while current metrics capture some aspects of robot navigation behavior, important subjective factors remain insufficiently represented and new metrics are necessary. Human-aware robot navigation is a key research area for integrating mobile robots into human environments [1], [2]. Beyond the classical challenges of path planning and obstacle avoidance, human-aware navigation must address qualitative aspects of social interaction, such as comfort, predictability, and personal space, which are difficult to capture with mathematical models [3], [4].
arXiv.org Artificial Intelligence
Oct-6-2025