2022/10/27 by Iaroslav Okunevich, Vincent Hilaire, Okunevich, Iaroslav +11
Psychology · Medicine · Computer Science · #Social Robot Interaction and HRI #Virology and Viral Diseases #Reinforcement Learning in Robotics
paper · pdf · doi:10.48550/arxiv.2210.15628
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.