SocNavBench: A Grounded Simulation Testing Framework for Evaluating Social Navigation
Abhijat Biswas, Allan Wang, Gustavo Silvera, Aaron Steinfeld, Henny, Admoni

TL;DR
SocNavBench is a simulation framework with realistic visuals and social scenarios, enabling consistent evaluation of social navigation algorithms through a suite of metrics, fostering comparison and development in the field.
Contribution
It introduces SocNavBench, a grounded simulation testing framework with curated scenarios and metrics, to standardize evaluation of social navigation methods.
Findings
Demonstrated testing of three existing methods and a baseline.
Showed how metrics reveal performance trade-offs.
Open-source code facilitates community contributions.
Abstract
The human-robot interaction (HRI) community has developed many methods for robots to navigate safely and socially alongside humans. However, experimental procedures to evaluate these works are usually constructed on a per-method basis. Such disparate evaluations make it difficult to compare the performance of such methods across the literature. To bridge this gap, we introduce SocNavBench, a simulation framework for evaluating social navigation algorithms. SocNavBench comprises a simulator with photo-realistic capabilities and curated social navigation scenarios grounded in real-world pedestrian data. We also provide an implementation of a suite of metrics to quantify the performance of navigation algorithms on these scenarios. Altogether, SocNavBench provides a test framework for evaluating disparate social navigation methods in a consistent and interpretable manner. To illustrate its…
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Taxonomy
TopicsSocial Robot Interaction and HRI · Evacuation and Crowd Dynamics · Innovative Human-Technology Interaction
