# Towards Data-Driven Metrics for Social Robot Navigation Benchmarking Source: [Towards Data-Driven Metrics for Social Robot Navigation Benchmarking]() Collection index: [llms.txt]() Data updated: 2026-07-08T05:00:20.838Z Authors: Pilar Bachiller-Burgos, Ulysses Bernardet, Luis V. Calderita, Pranup Chhetri, Anthony Francis, Noriaki Hirose, No\\'e P\\'erez, Dhruv Shah, Phani T. Singamaneni, Xuesu Xiao, Luis J. Manso Published: 2025-09-01T08:42:28.000Z ## Abstract This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy optimization for ground robots. We provide the motivations for our approach and describe our proposal to format and store rated social navigation trajectory datasets. Following these guidelines, we compiled a first version of the proposed dataset with 4427 trajectories -- 182 real and 4245 simulated -- and presented it to human raters, yielding a total of 4402 rated trajectories after data quality assurance. Notably, we provide the first all-encompassing learned social robot navigation metric (SN26), along qualitative and quantitative results, including the test loss achieved, a comparison against hand-crafted metrics, and an ablation study. All data, software, and model weights are publicly available. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Social Navigation Metric Evaluation on SocNav (test)](): Social Navigation Metric Evaluation; SocNav (test); Pearson Correlation (r): 0.797. ## Original sources and implementation [Original paper]() [PDF]()