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arXiv · 2605.06863

Bi3: A Biplatform, Bicultural, Biperson Dataset for Social Robot Navigation

Andrew Stratton·Phani Teja Singamaneni·Pranav Goyal·Rachid Alami·Christoforos Mavrogiannis
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Abstract

We contribute Bi3, a dataset of social robot navigation among groups of people in a constrained lab space. Compared to prior data collection efforts for social robot navigation, our dataset is unique in that it features: an original experiment design giving rise to close navigation encounters between two humans and a robot; five different navigation algorithms; two different robot platforms; a diverse participant pool of 74 people recruited from two sites in the USA and France; multimodal data streams including 10.5 hours of human and robot ground-truth motion tracks, RGB video, and user impressions over robot performance. Our analysis of the collected dataset through metrics like interaction density and human velocity suggests that Bi3 represents a benchmark of unique diversity and modeling complexity. Bi3 contributes towards understanding how humans and robots can productively mesh their activities in constrained environments, and can be a resource for training models of human motion prediction and robot control policies for navigation in densely crowded spaces.

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Andrew Stratton, Phani Teja Singamaneni, Pranav Goyal, Rachid Alami, Christoforos Mavrogiannis. 2026-05-07. Bi3: A Biplatform, Bicultural, Biperson Dataset for Social Robot Navigation. https://arxiv.org/abs/2605.06863

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