Human-centered Benchmarking for Socially-compliant Robot Navigation

TL;DR

This paper introduces a human-centered benchmarking framework for evaluating socially-compliant robot navigation, emphasizing social compatibility and reproducibility in experiments.

Contribution

It proposes a comprehensive benchmarking framework using RoSAS and validates metrics for assessing social compatibility in robot navigation.

Findings

Extra robot time ratio effectively measures social compatibility.

Extra distance ratio correlates with social compliance.

Benchmarking ensures reproducibility of social navigation assessments.

Abstract

Social compatibility is one of the most important parameters for service robots. It characterizes the quality of interaction between a robot and a human. In this paper, a human-centered benchmarking framework is proposed for socially-compliant robot navigation. In an end-to-end manner, four open-source robot navigation methods are benchmarked, two of which are socially-compliant. All aspects of the benchmarking are clarified to ensure the reproducibility and replicability of the experiments. The social compatibility of robot navigation methods with the Robotic Social Attributes Scale (RoSAS) is measured. After that, the correspondence between RoSAS and the robot-centered metrics is validated. Based on experiments, the extra robot time ratio and the extra distance ratio are the most suitable to judge social compatibility.