Authors:Pilar Bachiller-Burgos, Ulysses Bernardet, Luis V. Calderita, Pranup Chhetri, Anthony Francis, Noriaki Hirose, Noé Pérez, Dhruv Shah, Phani T. Singamaneni, Xuesu Xiao, Luis J. Manso
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.
From: Pilar Bachiller-Burgos [view email]
[v1]
Mon, 1 Sep 2025 08:42:28 UTC (2,058 KB)
[v2]
Wed, 31 Dec 2025 10:42:04 UTC (4,752 KB)
[v3]
Sun, 5 Jul 2026 17:07:06 UTC (3,168 KB)
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