Evaluation of social robot navigation inherently requires human input due to its qualitative nature. Motivated by the need to scale human evaluation, we propose a general method for deploying interactive, rich-client robotic simulations on the web. Prior approaches implement specific web-compatible simulators or provide tools to build a simulator for a specific study. Instead, our approach builds on standard Linux tools to share a graphical desktop with remote users. We leverage these tools to deploy simulators on the web that would typically be constrained to desktop computing environments. As an example implementation of our approach, we introduce the SEAN Experimental Platform (SEAN-EP). With SEAN-EP, remote users can virtually interact with a mobile robot in the Social Environment for Autonomous Navigation, without installing any software on their computer or needing specialized hardware. We validated that SEAN-EP could quickly scale the collection of human feedback and its usability through an online survey. In addition, we compared human feedback from participants that interacted with a robot using SEAN-EP with feedback obtained through a more traditional video survey. Our results suggest that human perceptions of robots may differ based on whether they interact with the robots in simulation or observe them in videos. Also, they suggest that people perceive the surveys with interactive simulations as less mentally demanding than video surveys.
翻译:社会机器人导航评估本身要求人由于其质量性质而进行人的投入。我们以扩大人类评价的需要为动力,提出在网络上部署互动、丰富客户机器人模拟的通用方法。先行方法采用特定的网络兼容模拟器,或提供工具,为特定研究建立模拟器。相反,我们的方法以标准的Linux工具为基础,与远程用户分享一张图形桌面。我们利用这些工具在网络上部署模拟器,这种模拟器通常局限于桌面计算环境。作为我们方法的范例,我们引入SEAN实验平台(SEAN-EP)。在SEAN-EP中,远程用户实际上可以与社会环境中的移动机器人互动,用于自主导航,而无需在计算机上安装任何软件或需要专门硬件。我们确认SEAN-EP可以通过在线调查迅速扩大人类反馈的收集量及其可用性。此外,我们用较传统的视频调查获得的反馈来比较了与机器人互动的参与者的人类反馈。我们的结果表明,人类对机器人的看法可能有所不同,因为他们在模拟中是否认为他们比模拟了他们更难的图像。